Encoder, decoder, encoding method, and decoding method

ABSTRACT

An encoder includes circuitry and memory. Using the memory, the circuitry: generates a reconstructed image by encoding and decoding an original image; performs, on a current block included in the reconstructed image, filter processing that is applied to all pixels in the current block, when an edge intensity of the current block is lower than a threshold; and skips the filter processing on the current block when the edge intensity of the current block is higher than the threshold.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a U.S. continuation application of PCT InternationalPatent Application Number PCT/JP2017/043557 filed on Dec. 5, 2017,claiming the benefit of priority of U.S. Provisional Patent ApplicationNo. 62/432,168 filed on Dec. 9, 2016, the entire contents of which arehereby incorporated by reference.

TECHNICAL FIELD

The present disclosure relates to an encoder, a decoder, an encodingmethod, and a decoding method.

BACKGROUND

Various examinations have been made for the High Efficiency Video Coding(HEVC) standard which is the latest video coding-standard standard, inorder to improve encoding efficiency (for example, see Non-patentLiterature (NPL) 1). The method is based on the InternationalTelecommunication Union Telecommunication Standardization Sector (ITU-T)standard represented by H.26x and the International Organization forStandardization/International Electrotechnical Commission (ISO/IEC)standard represented by MPEG-x, and has been examined as the next videoencoding standard subsequent to the standard represented by H.264/AVC orMPEG-4 AVC.

CITATION LIST Non-Patent Literature

-   [NPL 1] ITU-T Recommendation H.265 “High efficiency video coding”,    April, 2015-   [NPL 2] Joint Video Exploration Team (JVET) of ITU-T SG16 WP3 and    ISO/IEC JTC1/SC29/WG11 1nd Meeting: Geneva, CH, 19-21 Oct. 2015,    JVET-A1001, “Algorithm Description of Joint Exploration Test Model    1”

SUMMARY Technical Problem

There has been demand for such an encoding method and a decoding methodto achieve improvement in the quality of decoded images (reconstructedimages).

An object of the present disclosure is to provide an encoder, a decoder,an encoding method, and a decoding method that can improve the qualityof decoded images.

Solution to Problem

An encoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by encoding and decoding an original image;performs, on a current block included in the reconstructed image, filterprocessing that is applied to all pixels in the current block, when anedge intensity of the current block is lower than a threshold; and skipsthe filter processing on the current block when the edge intensity ofthe current block is higher than the threshold.

An encoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by encoding and decoding an original image;determines, based on an electro-optical transfer function (EOTF) of theoriginal image, a parameter for filter processing for a current blockincluded in the reconstructed image, the filter processing being to beapplied to all pixels in the current block; and performs, on the currentblock, the filter processing using the parameter determined.

A decoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by decoding encoded data; performs, on a currentblock included in the reconstructed image, filter processing that isapplied to all pixels in the current block, when an edge intensity ofthe current block is lower than a threshold; and skips the filterprocessing on the current block when the edge intensity of the currentblock is higher than the threshold.

A decoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by decoding encoded data; determines, based on anelectro-optical transfer function (EOTF) of the reconstructed image, aparameter for filter processing for a current block included in thereconstructed image, the filter processing being to be applied to allpixels in the current block; and performs, on the current block, thefilter processing using the parameter determined.

Note that these general and specific aspects may be implemented using asystem, a device, a method, an integrated circuit, a computer program,or a computer-readable non-transitory recording medium such as a CD-ROM,or any combination of systems, devices, methods, integrated circuits,computer programs, or computer-readable recording media.

Advantageous Effects

The present disclosure can provide an encoder, a decoder, an encodingmethod, and a decoding method that can improve the quality of decodedimages.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a block diagram illustrating a functional configuration of anencoder according to Embodiment 1.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1.

FIG. 3 is a chart indicating transform basis functions for eachtransform type.

FIG. 4A illustrates one example of a filter shape used in ALF.

FIG. 4B illustrates another example of a filter shape used in ALF.

FIG. 4C illustrates another example of a filter shape used in ALF.

FIG. 5A illustrates 67 intra prediction modes used in intra prediction.

FIG. 5B is a flow chart for illustrating an outline of a predictionimage correction process performed via OBMC processing.

FIG. 5C is a conceptual diagram for illustrating an outline of aprediction image correction process performed via OBMC processing.

FIG. 5D illustrates one example of FRUC.

FIG. 6 is for illustrating pattern matching (bilateral matching) betweentwo blocks along a motion trajectory.

FIG. 7 is for illustrating pattern matching (template matching) betweena template in the current picture and a block in a reference picture.

FIG. 8 is for illustrating a model assuming uniform linear motion.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks.

FIG. 9B is for illustrating an outline of a process for deriving amotion vector via merge mode.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

FIG. 10 is a block diagram illustrating a functional configuration of adecoder according to Embodiment 1.

FIG. 11A illustrates an example of a distribution of filter intensities.

FIG. 11B illustrates an example of a distribution of filter intensities.

FIG. 12 is a block diagram illustrating a loop filter according toEmbodiment 1.

FIG. 13 is a flowchart of filter processing according to Embodiment 1.

FIG. 14A illustrates an example of a reconstructed image according toEmbodiment 1.

FIG. 14B illustrates examples of edge intensities according toEmbodiment 1.

FIG. 14C illustrates examples of results of determining whether filterprocessing is ON or OFF according to Embodiment 1.

FIG. 15 is a block diagram of a loop filter according to Embodiment 2.

FIG. 16 is a flowchart of filter processing according to Embodiment 2.

FIG. 17 is a block diagram of a loop filter according to Embodiment 3.

FIG. 18 is a flowchart of filter processing according to Embodiment 3.

FIG. 19 is a block diagram of a loop filter according to Embodiment 4.

FIG. 20 is a flowchart of filter processing according to Embodiment 4.

FIG. 21 is a block diagram of a loop filter according to Embodiment 5.

FIG. 22 is a flowchart of filter processing according to Embodiment 5.

FIG. 23 is a block diagram of a loop filter according to Embodiment 6.

FIG. 24 is a flowchart of filter processing according to Embodiment 6.

FIG. 25 is a block diagram illustrating an example of implementation ofan encoder.

FIG. 26 is a block diagram illustrating an example of implementation ofa decoder.

FIG. 27 illustrates an overall configuration of a content providingsystem for implementing a content distribution service.

FIG. 28 illustrates one example of an encoding structure in scalableencoding.

FIG. 29 illustrates one example of an encoding structure in scalableencoding.

FIG. 30 illustrates an example of a display screen of a web page.

FIG. 31 illustrates an example of a display screen of a web page.

FIG. 32 illustrates one example of a smartphone.

FIG. 33 is a block diagram illustrating a configuration example of asmartphone.

DESCRIPTION OF EMBODIMENTS

(Underlying Knowledge Forming Basis of the Present Disclosure)

An adaptive loop filter (ALF) intended to bring a reconstructed imagecloser to an original image is one in-loop filter (for example, see NPL2). With ALF, one of filters having five-level strengths is applied to acurrent block, based on an edge intensity of the current blockcalculated from the values of peripheral pixels. Specifically, thecalculated edge intensity is first clipped to the value in a range from0 to 15. The clipped value is classified into one of five-level fixedgroups. Among the filters having five-level strengths, a filter for thegroup into which the clipped value is classified is applied to thecurrent block.

However, according to the above technique, when the calculated edgeintensities are 16 or higher, all the intensities are clipped to 15, andthus the same filter is applied to all the blocks having the edgeintensities of 16 or higher. Here, a filter often does not suit when theedge intensity is very high (for example, when the edge intensity is 30or higher). Accordingly, a difference between a filtered image and anoriginal image may be greater than the difference between the imagebefore being filtered and the original image.

FIGS. 11A and 11B illustrate examples of distributions of unclipped edgeintensities that are edge intensities before being clipped. In theexample illustrated in FIG. 11A, a percentage of blocks having edgeintensities of 16 or higher is low. Accordingly, filter processing canbe appropriately performed using the technique described above. On theother hand, as illustrated in FIG. 11B, when the percentage of blockshaving edge intensities of 16 or higher is high, and the edgeintensities are broadly distributed, the same filter is applied to allthe edge intensities of 16 or higher. Accordingly, it is difficult toapply the most suitable filter, and a block greatly different from anoriginal image may be generated by applying such an unsuited filter.

In addition, the clipped edge intensities are grouped at five levelsfixedly, yet the same fixed groups are used even for, for example, astandard dynamic range (SDR) video and a high dynamic range (HDR) videothat have sequences with different distributions of edge intensities,and thus filter design may be turned out to be unsuitable for thedistributions of edge intensities.

An encoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by encoding and decoding an original image;performs, on a current block included in the reconstructed image, filterprocessing that is applied to all pixels in the current block, when anedge intensity of the current block is lower than a threshold; and skipsthe filter processing on the current block when the edge intensity ofthe current block is higher than the threshold.

According to this, filter processing is not performed on a block havinga high edge intensity. Accordingly, for example, filter processing canbe prevented from being performed on a block which may be greatlydifferent from an original image due to being subjected to filterprocessing. Accordingly, the quality of decoded images can be improved.

For example, in the filter processing, filters to be used may beassociated with groups that are ranges of edge intensities, a group thatincludes the edge intensity of the current block may be determined fromamong the groups, and one of the filters that is associated with thegroup determined to include the edge intensity of the current block maybe used for the current block.

For example, in determining the group, the edge intensity may be clippedto a predetermined value, and a group that includes the edge intensityclipped may be determined, the filter processing may be performed on thecurrent block when the edge intensity before being clipped is lower thanthe threshold, and the filter processing on the current block may beskipped when the edge intensity before being clipped is higher than thethreshold.

For example, the threshold may be higher than the predetermined value.

For example, the circuitry may further determine the threshold, andgenerate an encoded bitstream that includes information indicating thethreshold determined.

According to this, an appropriate threshold can be determined, and thuswhether filter processing is performed can be appropriately determinedusing the threshold.

For example, the circuitry may further: calculate, based on edgeintensities of blocks included in a processing unit, a statistic of theedge intensities for the processing unit; and perform the filterprocessing on all the blocks included in the processing unit when thestatistic satisfies a predetermined condition.

According to this, whether or not to perform determination processing ofdetermining whether to perform filter processing can be switched basedon a statistic. Accordingly, the frequency of occurrence of thedetermination processing can be reduced, and thus an increase in theamount of processing due to the determination processing can beinhibited.

For example, the circuitry may further determine a parameter for thefilter processing for the current block, based on an electro-opticaltransfer function (EOTF) of the original image.

According to this, for each of the sequences having differentdistributions of edge intensities, filter processing suitable for thesequence can be performed.

An encoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by encoding and decoding an original image;determines, based on an electro-optical transfer function (EOTF) of theoriginal image, a parameter for filter processing for a current blockincluded in the reconstructed image, the filter processing being to beapplied to all pixels in the current block; and performs, on the currentblock, the filter processing using the parameter determined.

According to this, for each of the sequences having differentdistributions of edge intensities, filter processing suitable for thesequence can be performed. Accordingly, the quality of decoded imagescan be improved.

For example, in the filter processing, filters to be used may beassociated with groups that are ranges of edge intensities, a group thatincludes an edge intensity of the current block may be determined fromamong the groups, a filter associated with the group determined toinclude the edge intensity of the current block may be used for thecurrent block, and the parameter may be according to the groups.

A decoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by decoding encoded data; performs, on a currentblock included in the reconstructed image, filter processing that isapplied to all pixels in the current block, when an edge intensity ofthe current block is lower than a threshold; and skips the filterprocessing on the current block when the edge intensity of the currentblock is higher than the threshold.

According to this, filter processing is not performed on a block havinga high edge intensity. Accordingly, for example, filter processing canbe prevented from being performed on a block which may be greatlydifferent from an original image due to being subjected to filterprocessing. Accordingly, the quality of decoded images can be improved.

For example, in the filter processing, filters to be used may beassociated with groups that are ranges of edge intensities, a group thatincludes the edge intensity of the current block may be determined fromamong the groups, and one of the filters that is associated with thegroup determined to include the edge intensity of the current block maybe used for the current block.

For example, in determining the group, the edge intensity may be clippedto a predetermined value, and a group that includes the edge intensityclipped may be determined, the filter processing may be performed on thecurrent block when the edge intensity before being clipped is lower thanthe threshold, and the filter processing on the current block may beskipped when the edge intensity before being clipped is higher than thethreshold.

For example, the threshold may be higher than the predetermined value.

For example, the circuitry may further obtain information indicating thethreshold from an encoded bitstream that includes the encoded data.

According to this, since an appropriate threshold can be determined,whether to perform filter processing can be appropriately determinedusing the threshold.

For example, the circuitry may further: calculate, based on edgeintensities of blocks included in a processing unit, a statistic of theedge intensities for the processing unit; and perform the filterprocessing on all the blocks included in the processing unit when thestatistic satisfies a predetermined condition.

According to this, whether or not to perform determination processing ofdetermining whether to perform filter processing can be switched basedon a statistic. Accordingly, the frequency of occurrence of thedetermination processing can be reduced, and thus an increase in theamount of processing due to the determination processing can beinhibited.

For example, the circuitry may further determine a parameter for thefilter processing for the current block, based on an electro-opticaltransfer function (EOTF) of the reconstructed image.

According to this, for each of the sequences having differentdistributions of edge intensities, filter processing suitable for thesequence can be performed.

A decoder according to an aspect of the present disclosure includes:circuitry; and memory. Using the memory, the circuitry: generates areconstructed image by decoding encoded data; determines, based on anelectro-optical transfer function (EOTF) of the reconstructed image, aparameter for filter processing for a current block included in thereconstructed image, the filter processing being to be applied to allpixels in the current block; and performs, on the current block, thefilter processing using the parameter determined.

According to this, for each of the sequences having differentdistributions of edge intensities, filter processing suitable for thesequence can be performed. Accordingly, the quality of decoded imagescan be improved.

For example, in the filter processing, filters to be used may beassociated with groups that are ranges of edge intensities, a group thatincludes an edge intensity of the current block may be determined fromamong the groups, one of the filters that is associated with the groupdetermined to include the edge intensity of the current block may beused for the current block, and the parameter may be according to thegroups.

An encoding method according to an aspect of the present disclosureincludes: generating a reconstructed image by encoding and decoding anoriginal image; performing, on a current block included in thereconstructed image, filter processing that is applied to all pixels inthe current block, when an edge intensity of the current block is lowerthan a threshold; and skipping the filter processing on the currentblock when the edge intensity of the current block is higher than thethreshold.

According to this, filter processing is not performed on a block havinga high edge intensity. Accordingly, for example, filter processing canbe prevented from being performed on a block which may be greatlydifferent from an original image due to being subjected to filterprocessing. Accordingly, the quality of decoded images can be improved.

An encoding method according to an aspect of the present disclosureincludes: generating a reconstructed image by encoding and decoding anoriginal image; determining, based on an electro-optical transferfunction (EOTF) of the original image, a parameter for filter processingfor a current block included in the reconstructed image, the filterprocessing being to be applied to all pixels in the current block; andperforming the filter processing on the current block, using theparameter determined.

According to this, for each of the sequences having differentdistributions of edge intensities, filter processing suitable for thesequence can be performed. Accordingly, the quality of decoded imagescan be improved.

A decoding method according to an aspect of the present disclosureincludes: generating a reconstructed image by decoding encoded data;performing, on a current block included in the reconstructed image,filter processing that is applied to all pixels in the current block,when an edge intensity of the current block is lower than a threshold;and skipping the filter processing on the current block when the edgeintensity of the current block is higher than the threshold.

According to this, filter processing is not performed on a block havinga high edge intensity. Accordingly, for example, filter processing canbe prevented from being performed on a block which may be greatlydifferent from an original image due to being subjected to filterprocessing. Accordingly, the quality of decoded images can be improved.

A decoding method according to an aspect of the present disclosureincludes: generating a reconstructed image by decoding encoded data;determining, based on an electro-optical transfer function (EOTF) of thereconstructed image, a parameter for filter processing for a currentblock included in the reconstructed image, the filter processing beingto be applied to all pixels in the current block; and performing thefilter processing on the current block, using the parameter determined.

According to this, for each of the sequences having differentdistributions of edge intensities, filter processing suitable for thesequence can be performed. Accordingly, the quality of decoded imagescan be improved.

Furthermore, these general and specific aspects may be implemented usinga system, a device, a method, an integrated circuit, a computer program,or a non-transitory computer-readable recording medium such as a CD-ROM,or any combination of systems, devices, methods, integrated circuits,computer programs, or recording media.

Hereinafter, embodiments will be described with reference to thedrawings.

Note that the embodiments described below each show a general orspecific example. The numerical values, shapes, materials, components,the arrangement and connection of the components, steps, order of thesteps, etc., indicated in the following embodiments are mere examples,and therefore are not intended to limit the scope of the claims.Therefore, among the components in the following embodiments, those notrecited in any of the independent claims defining the broadest inventiveconcepts are described as optional components.

Embodiment 1

First, an outline of Embodiment 1 will be presented. Embodiment 1 is oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in subsequent description of aspects of thepresent disclosure are applicable. Note that Embodiment 1 is merely oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in the description of aspects of the presentdisclosure are applicable. The processes and/or configurations presentedin the description of aspects of the present disclosure can also beimplemented in an encoder and a decoder different from those accordingto Embodiment 1.

When the processes and/or configurations presented in the description ofaspects of the present disclosure are applied to Embodiment 1, forexample, any of the following may be performed.

(1) regarding the encoder or the decoder according to Embodiment 1,among components included in the encoder or the decoder according toEmbodiment 1, substituting a component corresponding to a componentpresented in the description of aspects of the present disclosure with acomponent presented in the description of aspects of the presentdisclosure;

(2) regarding the encoder or the decoder according to Embodiment 1,implementing discretionary changes to functions or implemented processesperformed by one or more components included in the encoder or thedecoder according to Embodiment 1, such as addition, substitution, orremoval, etc., of such functions or implemented processes, thensubstituting a component corresponding to a component presented in thedescription of aspects of the present disclosure with a componentpresented in the description of aspects of the present disclosure;

(3) regarding the method implemented by the encoder or the decoderaccording to Embodiment 1, implementing discretionary changes such asaddition of processes and/or substitution, removal of one or more of theprocesses included in the method, and then substituting a processescorresponding to a process presented in the description of aspects ofthe present disclosure with a process presented in the description ofaspects of the present disclosure;

(4) combining one or more components included in the encoder or thedecoder according to Embodiment 1 with a component presented in thedescription of aspects of the present disclosure, a component includingone or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(5) combining a component including one or more functions included inone or more components included in the encoder or the decoder accordingto Embodiment 1, or a component that implements one or more processesimplemented by one or more components included in the encoder or thedecoder according to Embodiment 1 with a component presented in thedescription of aspects of the present disclosure, a component includingone or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(6) regarding the method implemented by the encoder or the decoderaccording to Embodiment 1, among processes included in the method,substituting a process corresponding to a process presented in thedescription of aspects of the present disclosure with a processpresented in the description of aspects of the present disclosure; and

(7) combining one or more processes included in the method implementedby the encoder or the decoder according to Embodiment 1 with a processpresented in the description of aspects of the present disclosure.

Note that the implementation of the processes and/or configurationspresented in the description of aspects of the present disclosure is notlimited to the above examples. For example, the processes and/orconfigurations presented in the description of aspects of the presentdisclosure may be implemented in a device used for a purpose differentfrom the moving picture/picture encoder or the moving picture/picturedecoder disclosed in Embodiment 1. Moreover, the processes and/orconfigurations presented in the description of aspects of the presentdisclosure may be independently implemented. Moreover, processes and/orconfigurations described in different aspects may be combined.

[Encoder Outline]

First, the encoder according to Embodiment 1 will be outlined. FIG. 1 isa block diagram illustrating a functional configuration of encoder 100according to Embodiment 1. Encoder 100 is a moving picture/pictureencoder that encodes a moving picture/picture block by block.

As illustrated in FIG. 1, encoder 100 is a device that encodes a pictureblock by block, and includes splitter 102, subtractor 104, transformer106, quantizer 108, entropy encoder 110, inverse quantizer 112, inversetransformer 114, adder 116, block memory 118, loop filter 120, framememory 122, intra predictor 124, inter predictor 126, and predictioncontroller 128.

Encoder 100 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as splitter 102, subtractor104, transformer 106, quantizer 108, entropy encoder 110, inversequantizer 112, inverse transformer 114, adder 116, loop filter 120,intra predictor 124, inter predictor 126, and prediction controller 128.Alternatively, encoder 100 may be realized as one or more dedicatedelectronic circuits corresponding to splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, loop filter 120, intrapredictor 124, inter predictor 126, and prediction controller 128.

Hereinafter, each component included in encoder 100 will be described.

[Splitter]

Splitter 102 splits each picture included in an input moving pictureinto blocks, and outputs each block to subtractor 104. For example,splitter 102 first splits a picture into blocks of a fixed size (forexample, 128×128). The fixed size block is also referred to as codingtree unit (CTU). Splitter 102 then splits each fixed size block intoblocks of variable sizes (for example, 64×64 or smaller), based onrecursive quadtree and/or binary tree block splitting. The variable sizeblock is also referred to as a coding unit (CU), a prediction unit (PU),or a transform unit (TU). Note that in this embodiment, there is no needto differentiate between CU, PU, and TU; all or some of the blocks in apicture may be processed per CU, PU, or TU.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1. In FIG. 2, the solid lines represent block boundaries ofblocks split by quadtree block splitting, and the dashed lines representblock boundaries of blocks split by binary tree block splitting.

Here, block 10 is a square 128×128 pixel block (128×128 block). This128×128 block 10 is first split into four square 64×64 blocks (quadtreeblock splitting).

The top left 64×64 block is further vertically split into two rectangle32×64 blocks, and the left 32×64 block is further vertically split intotwo rectangle 16×64 blocks (binary tree block splitting). As a result,the top left 64×64 block is split into two 16×64 blocks 11 and 12 andone 32×64 block 13.

The top right 64×64 block is horizontally split into two rectangle 64×32blocks 14 and 15 (binary tree block splitting).

The bottom left 64×64 block is first split into four square 32×32 blocks(quadtree block splitting). The top left block and the bottom rightblock among the four 32×32 blocks are further split. The top left 32×32block is vertically split into two rectangle 16×32 blocks, and the right16×32 block is further horizontally split into two 16×16 blocks (binarytree block splitting). The bottom right 32×32 block is horizontallysplit into two 32×16 blocks (binary tree block splitting). As a result,the bottom left 64×64 block is split into 16×32 block 16, two 16×16blocks 17 and 18, two 32×32 blocks 19 and 20, and two 32×16 blocks 21and 22.

The bottom right 64×64 block 23 is not split.

As described above, in FIG. 2, block 10 is split into 13 variable sizeblocks 11 through 23 based on recursive quadtree and binary tree blocksplitting. This type of splitting is also referred to as quadtree plusbinary tree (QTBT) splitting.

Note that in FIG. 2, one block is split into four or two blocks(quadtree or binary tree block splitting), but splitting is not limitedto this example. For example, one block may be split into three blocks(ternary block splitting). Splitting including such ternary blocksplitting is also referred to as multi-type tree (MBT) splitting.

[Subtractor]

Subtractor 104 subtracts a prediction signal (prediction sample) from anoriginal signal (original sample) per block split by splitter 102. Inother words, subtractor 104 calculates prediction errors (also referredto as residuals) of a block to be encoded (hereinafter referred to as acurrent block). Subtractor 104 then outputs the calculated predictionerrors to transformer 106.

The original signal is a signal input into encoder 100, and is a signalrepresenting an image for each picture included in a moving picture (forexample, a luma signal and two chroma signals). Hereinafter, a signalrepresenting an image is also referred to as a sample.

[Transformer]

Transformer 106 transforms spatial domain prediction errors intofrequency domain transform coefficients, and outputs the transformcoefficients to quantizer 108. More specifically, transformer 106applies, for example, a predefined discrete cosine transform (DCT) ordiscrete sine transform (DST) to spatial domain prediction errors.

Note that transformer 106 may adaptively select a transform type fromamong a plurality of transform types, and transform prediction errorsinto transform coefficients by using a transform basis functioncorresponding to the selected transform type. This sort of transform isalso referred to as explicit multiple core transform (EMT) or adaptivemultiple transform (AMT).

The transform types include, for example, DCT-II, DCT-V, DCT-VIII,DST-I, and DST-VII. FIG. 3 is a chart indicating transform basisfunctions for each transform type. In FIG. 3, N indicates the number ofinput pixels. For example, selection of a transform type from among theplurality of transform types may depend on the prediction type (intraprediction and inter prediction), and may depend on intra predictionmode.

Information indicating whether to apply such EMT or AMT (referred to as,for example, an AMT flag) and information indicating the selectedtransform type is signalled at the CU level. Note that the signaling ofsuch information need not be performed at the CU level, and may beperformed at another level (for example, at the sequence level, picturelevel, slice level, tile level, or CTU level).

Moreover, transformer 106 may apply a secondary transform to thetransform coefficients (transform result). Such a secondary transform isalso referred to as adaptive secondary transform (AST) or non-separablesecondary transform (NSST). For example, transformer 106 applies asecondary transform to each sub-block (for example, each 4×4 sub-block)included in the block of the transform coefficients corresponding to theintra prediction errors. Information indicating whether to apply NSSTand information related to the transform matrix used in NSST aresignalled at the CU level. Note that the signaling of such informationneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, or CTU level).

Here, a separable transform is a method in which a transform isperformed a plurality of times by separately performing a transform foreach direction according to the number of dimensions input. Anon-separable transform is a method of performing a collective transformin which two or more dimensions in a multidimensional input arecollectively regarded as a single dimension.

In one example of a non-separable transform, when the input is a 4×4block, the 4×4 block is regarded as a single array including 16components, and the transform applies a 16×16 transform matrix to thearray.

Moreover, similar to above, after an input 4×4 block is regarded as asingle array including 16 components, a transform that performs aplurality of Givens rotations on the array (i.e., a Hypercube-GivensTransform) is also one example of a non-separable transform.

[Quantizer]

Quantizer 108 quantizes the transform coefficients output fromtransformer 106. More specifically, quantizer 108 scans, in apredetermined scanning order, the transform coefficients of the currentblock, and quantizes the scanned transform coefficients based onquantization parameters (QP) corresponding to the transformcoefficients. Quantizer 108 then outputs the quantized transformcoefficients (hereinafter referred to as quantized coefficients) of thecurrent block to entropy encoder 110 and inverse quantizer 112.

A predetermined order is an order for quantizing/inverse quantizingtransform coefficients. For example, a predetermined scanning order isdefined as ascending order of frequency (from low to high frequency) ordescending order of frequency (from high to low frequency).

A quantization parameter is a parameter defining a quantization stepsize (quantization width). For example, if the value of the quantizationparameter increases, the quantization step size also increases. In otherwords, if the value of the quantization parameter increases, thequantization error increases.

[Entropy Encoder]

Entropy encoder 110 generates an encoded signal (encoded bitstream) byvariable length encoding quantized coefficients, which are inputs fromquantizer 108. More specifically, entropy encoder 110, for example,binarizes quantized coefficients and arithmetic encodes the binarysignal.

[Inverse Quantizer]

Inverse quantizer 112 inverse quantizes quantized coefficients, whichare inputs from quantizer 108. More specifically, inverse quantizer 112inverse quantizes, in a predetermined scanning order, quantizedcoefficients of the current block. Inverse quantizer 112 then outputsthe inverse quantized transform coefficients of the current block toinverse transformer 114.

[Inverse Transformer]

Inverse transformer 114 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 112. More specifically, inverse transformer 114 restores theprediction errors of the current block by applying an inverse transformcorresponding to the transform applied by transformer 106 on thetransform coefficients. Inverse transformer 114 then outputs therestored prediction errors to adder 116.

Note that since information is lost in quantization, the restoredprediction errors do not match the prediction errors calculated bysubtractor 104. In other words, the restored prediction errors includequantization errors.

[Adder]

Adder 116 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 114, and prediction samples,which are inputs from prediction controller 128. Adder 116 then outputsthe reconstructed block to block memory 118 and loop filter 120. Areconstructed block is also referred to as a local decoded block.

[Block Memory]

Block memory 118 is storage for storing blocks in a picture to beencoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 118 storesreconstructed blocks output from adder 116.

[Loop Filter]

Loop filter 120 applies a loop filter to blocks reconstructed by adder116, and outputs the filtered reconstructed blocks to frame memory 122.A loop filter is a filter used in an encoding loop (in-loop filter), andincludes, for example, a deblocking filter (DF), a sample adaptiveoffset (SAO), and an adaptive loop filter (ALF).

In ALF, a least square error filter for removing compression artifactsis applied. For example, one filter from among a plurality of filters isselected for each 2×2 sub-block in the current block based on directionand activity of local gradients, and is applied.

More specifically, first, each sub-block (for example, each 2×2sub-block) is categorized into one out of a plurality of classes (forexample, 15 or 25 classes). The classification of the sub-block is basedon gradient directionality and activity. For example, classificationindex C is derived based on gradient directionality D (for example, 0 to2 or 0 to 4) and gradient activity A (for example, 0 to 4) (for example,C=5D+A). Then, based on classification index C, each sub-block iscategorized into one out of a plurality of classes (for example, 15 or25 classes).

For example, gradient directionality D is calculated by comparinggradients of a plurality of directions (for example, the horizontal,vertical, and two diagonal directions). Moreover, for example, gradientactivity A is calculated by summing gradients of a plurality ofdirections and quantizing the sum.

The filter to be used for each sub-block is determined from among theplurality of filters based on the result of such categorization.

The filter shape to be used in ALF is, for example, a circular symmetricfilter shape. FIG. 4A through FIG. 4C illustrate examples of filtershapes used in ALF. FIG. 4A illustrates a 5×5 diamond shape filter, FIG.4B illustrates a 7×7 diamond shape filter, and FIG. 4C illustrates a 9×9diamond shape filter. Information indicating the filter shape issignalled at the picture level. Note that the signaling of informationindicating the filter shape need not be performed at the picture level,and may be performed at another level (for example, at the sequencelevel, slice level, tile level, CTU level, or CU level).

The enabling or disabling of ALF is determined at the picture level orCU level. For example, for luma, the decision to apply ALF or not isdone at the CU level, and for chroma, the decision to apply ALF or notis done at the picture level. Information indicating whether ALF isenabled or disabled is signalled at the picture level or CU level. Notethat the signaling of information indicating whether ALF is enabled ordisabled need not be performed at the picture level or CU level, and maybe performed at another level (for example, at the sequence level, slicelevel, tile level, or CTU level).

The coefficients set for the plurality of selectable filters (forexample, 15 or 25 filters) is signalled at the picture level. Note thatthe signaling of the coefficients set need not be performed at thepicture level, and may be performed at another level (for example, atthe sequence level, slice level, tile level, CTU level, CU level, orsub-block level).

[Frame Memory]

Frame memory 122 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 122 stores reconstructed blocks filtered byloop filter 120.

[Intra Predictor]

Intra predictor 124 generates a prediction signal (intra predictionsignal) by intra predicting the current block with reference to a blockor blocks in the current picture and stored in block memory 118 (alsoreferred to as intra frame prediction). More specifically, intrapredictor 124 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 128.

For example, intra predictor 124 performs intra prediction by using onemode from among a plurality of predefined intra prediction modes. Theintra prediction modes include one or more non-directional predictionmodes and a plurality of directional prediction modes.

The one or more non-directional prediction modes include, for example,planar prediction mode and DC prediction mode defined in theH.265/high-efficiency video coding (HEVC) standard (see NPL 1).

The plurality of directional prediction modes include, for example, the33 directional prediction modes defined in the H.265/HEVC standard. Notethat the plurality of directional prediction modes may further include32 directional prediction modes in addition to the 33 directionalprediction modes (for a total of 65 directional prediction modes). FIG.5A illustrates 67 intra prediction modes used in intra prediction (twonon-directional prediction modes and 65 directional prediction modes).The solid arrows represent the 33 directions defined in the H.265/HEVCstandard, and the dashed arrows represent the additional 32 directions.

Note that a luma block may be referenced in chroma block intraprediction. In other words, a chroma component of the current block maybe predicted based on a luma component of the current block. Such intraprediction is also referred to as cross-component linear model (CCLM)prediction. Such a chroma block intra prediction mode that references aluma block (referred to as, for example, CCLM mode) may be added as oneof the chroma block intra prediction modes.

Intra predictor 124 may correct post-intra-prediction pixel values basedon horizontal/vertical reference pixel gradients. Intra predictionaccompanied by this sort of correcting is also referred to as positiondependent intra prediction combination (PDPC). Information indicatingwhether to apply PDPC or not (referred to as, for example, a PDPC flag)is, for example, signalled at the CU level. Note that the signaling ofthis information need not be performed at the CU level, and may beperformed at another level (for example, on the sequence level, picturelevel, slice level, tile level, or CTU level).

[Inter Predictor]

Inter predictor 126 generates a prediction signal (inter predictionsignal) by inter predicting the current block with reference to a blockor blocks in a reference picture, which is different from the currentpicture and is stored in frame memory 122 (also referred to as interframe prediction). Inter prediction is performed per current block orper sub-block (for example, per 4×4 block) in the current block. Forexample, inter predictor 126 performs motion estimation in a referencepicture for the current block or sub-block. Inter predictor 126 thengenerates an inter prediction signal of the current block or sub-blockby motion compensation by using motion information (for example, amotion vector) obtained from motion estimation. Inter predictor 126 thenoutputs the generated inter prediction signal to prediction controller128.

The motion information used in motion compensation is signalled. Amotion vector predictor may be used for the signaling of the motionvector. In other words, the difference between the motion vector and themotion vector predictor may be signalled.

Note that the inter prediction signal may be generated using motioninformation for a neighboring block in addition to motion informationfor the current block obtained from motion estimation. Morespecifically, the inter prediction signal may be generated per sub-blockin the current block by calculating a weighted sum of a predictionsignal based on motion information obtained from motion estimation and aprediction signal based on motion information for a neighboring block.Such inter prediction (motion compensation) is also referred to asoverlapped block motion compensation (OBMC).

In such an OBMC mode, information indicating sub-block size for OBMC(referred to as, for example, OBMC block size) is signalled at thesequence level. Moreover, information indicating whether to apply theOBMC mode or not (referred to as, for example, an OBMC flag) issignalled at the CU level. Note that the signaling of such informationneed not be performed at the sequence level and CU level, and may beperformed at another level (for example, at the picture level, slicelevel, tile level, CTU level, or sub-block level).

Hereinafter, the OBMC mode will be described in further detail. FIG. 5Bis a flowchart and FIG. 5C is a conceptual diagram for illustrating anoutline of a prediction image correction process performed via OBMCprocessing.

First, a prediction image (Pred) is obtained through typical motioncompensation using a motion vector (MV) assigned to the current block.

Next, a prediction image (Pred_L) is obtained by applying a motionvector (MV_L) of the encoded neighboring left block to the currentblock, and a first pass of the correction of the prediction image ismade by superimposing the prediction image and Pred_L.

Similarly, a prediction image (Pred_U) is obtained by applying a motionvector (MV_U) of the encoded neighboring upper block to the currentblock, and a second pass of the correction of the prediction image ismade by superimposing the prediction image resulting from the first passand Pred_U. The result of the second pass is the final prediction image.

Note that the above example is of a two-pass correction method using theneighboring left and upper blocks, but the method may be a three-pass orhigher correction method that also uses the neighboring right and/orlower block.

Note that the region subject to superimposition may be the entire pixelregion of the block, and, alternatively, may be a partial block boundaryregion.

Note that here, the prediction image correction process is described asbeing based on a single reference picture, but the same applies when aprediction image is corrected based on a plurality of referencepictures. In such a case, after corrected prediction images resultingfrom performing correction based on each of the reference pictures areobtained, the obtained corrected prediction images are furthersuperimposed to obtain the final prediction image.

Note that the unit of the current block may be a prediction block and,alternatively, may be a sub-block obtained by further dividing theprediction block.

One example of a method for determining whether to implement OBMCprocessing is by using an obmc_flag, which is a signal that indicateswhether to implement OBMC processing. As one specific example, theencoder determines whether the current block belongs to a regionincluding complicated motion. The encoder sets the obmc_flag to a valueof “1” when the block belongs to a region including complicated motionand implements OBMC processing when encoding, and sets the obmc_flag toa value of “0” when the block does not belong to a region includingcomplication motion and encodes without implementing OBMC processing.The decoder switches between implementing OBMC processing or not bydecoding the obmc_flag written in the stream and performing the decodingin accordance with the flag value.

Note that the motion information may be derived on the decoder sidewithout being signalled. For example, a merge mode defined in theH.265/HEVC standard may be used. Moreover, for example, the motioninformation may be derived by performing motion estimation on thedecoder side. In this case, motion estimation is performed without usingthe pixel values of the current block.

Here, a mode for performing motion estimation on the decoder side willbe described. A mode for performing motion estimation on the decoderside is also referred to as pattern matched motion vector derivation(PMMVD) mode or frame rate up-conversion (FRUC) mode.

One example of FRUC processing is illustrated in FIG. 5D. First, acandidate list (a candidate list may be a merge list) of candidates eachincluding a motion vector predictor is generated with reference tomotion vectors of encoded blocks that spatially or temporally neighborthe current block. Next, the best candidate MV is selected from among aplurality of candidate MVs registered in the candidate list. Forexample, evaluation values for the candidates included in the candidatelist are calculated and one candidate is selected based on thecalculated evaluation values.

Next, a motion vector for the current block is derived from the motionvector of the selected candidate. More specifically, for example, themotion vector for the current block is calculated as the motion vectorof the selected candidate (best candidate MV), as-is. Alternatively, themotion vector for the current block may be derived by pattern matchingperformed in the vicinity of a position in a reference picturecorresponding to the motion vector of the selected candidate. In otherwords, when the vicinity of the best candidate MV is searched via thesame method and an MV having a better evaluation value is found, thebest candidate MV may be updated to the MV having the better evaluationvalue, and the MV having the better evaluation value may be used as thefinal MV for the current block. Note that a configuration in which thisprocessing is not implemented is also acceptable.

The same processes may be performed in cases in which the processing isperformed in units of sub-blocks.

Note that an evaluation value is calculated by calculating thedifference in the reconstructed image by pattern matching performedbetween a region in a reference picture corresponding to a motion vectorand a predetermined region. Note that the evaluation value may becalculated by using some other information in addition to thedifference.

The pattern matching used is either first pattern matching or secondpattern matching. First pattern matching and second pattern matching arealso referred to as bilateral matching and template matching,respectively.

In the first pattern matching, pattern matching is performed between twoblocks along the motion trajectory of the current block in two differentreference pictures. Therefore, in the first pattern matching, a regionin another reference picture conforming to the motion trajectory of thecurrent block is used as the predetermined region for theabove-described calculation of the candidate evaluation value.

FIG. 6 is for illustrating one example of pattern matching (bilateralmatching) between two blocks along a motion trajectory. As illustratedin FIG. 6, in the first pattern matching, two motion vectors (MV0, MV1)are derived by finding the best match between two blocks along themotion trajectory of the current block (Cur block) in two differentreference pictures (Ref0, Ref1). More specifically, a difference between(i) a reconstructed image in a specified position in a first encodedreference picture (Ref0) specified by a candidate MV and (ii) areconstructed picture in a specified position in a second encodedreference picture (Ref1) specified by a symmetrical MV scaled at adisplay time interval of the candidate MV may be derived, and theevaluation value for the current block may be calculated by using thederived difference. The candidate MV having the best evaluation valueamong the plurality of candidate MVs may be selected as the final MV.

Under the assumption of continuous motion trajectory, the motion vectors(MV0, MV1) pointing to the two reference blocks shall be proportional tothe temporal distances (TD0, TD1) between the current picture (Cur Pic)and the two reference pictures (Ref0, Ref1). For example, when thecurrent picture is temporally between the two reference pictures and thetemporal distance from the current picture to the two reference picturesis the same, the first pattern matching derives a mirror basedbi-directional motion vector.

In the second pattern matching, pattern matching is performed between atemplate in the current picture (blocks neighboring the current block inthe current picture (for example, the top and/or left neighboringblocks)) and a block in a reference picture. Therefore, in the secondpattern matching, a block neighboring the current block in the currentpicture is used as the predetermined region for the above-describedcalculation of the candidate evaluation value.

FIG. 7 is for illustrating one example of pattern matching (templatematching) between a template in the current picture and a block in areference picture. As illustrated in FIG. 7, in the second patternmatching, a motion vector of the current block is derived by searching areference picture (Ref0) to find the block that best matches neighboringblocks of the current block (Cur block) in the current picture (CurPic). More specifically, a difference between (i) a reconstructed imageof an encoded region that is both or one of the neighboring left andneighboring upper region and (ii) a reconstructed picture in the sameposition in an encoded reference picture (Ref0) specified by a candidateMV may be derived, and the evaluation value for the current block may becalculated by using the derived difference. The candidate MV having thebest evaluation value among the plurality of candidate MVs may beselected as the best candidate MV.

Information indicating whether to apply the FRUC mode or not (referredto as, for example, a FRUC flag) is signalled at the CU level. Moreover,when the FRUC mode is applied (for example, when the FRUC flag is set totrue), information indicating the pattern matching method (first patternmatching or second pattern matching) is signalled at the CU level. Notethat the signaling of such information need not be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, CTU level, orsub-block level).

Here, a mode for deriving a motion vector based on a model assuminguniform linear motion will be described. This mode is also referred toas a bi-directional optical flow (BIO) mode.

FIG. 8 is for illustrating a model assuming uniform linear motion. InFIG. 8, (v_(x), v_(y)) denotes a velocity vector, and τ₀ and τ₁ denotetemporal distances between the current picture (Cur Pic) and tworeference pictures (Ref₀, Ref₁). (MVx₀, MVy₀) denotes a motion vectorcorresponding to reference picture Ref₀, and (MVx₁, MVy₁) denotes amotion vector corresponding to reference picture Ref₁.

Here, under the assumption of uniform linear motion exhibited byvelocity vector (v_(x), v_(y)), (MVx₀, MVy₀) and (MVx₁, MVy₁) arerepresented as (v_(x)τ₀, v_(y)τ₀) and (−v_(x)τ₁, −v_(y)τ₁),respectively, and the following optical flow equation is given.MATH. 1∂I ^((k)) /∂t+v _(x) ∂I ^((k)) /∂x+v _(y) ∂I ^((k)) /∂y=0.  (1)

Here, I^((k)) denotes a luma value from reference picture k (k=0, 1)after motion compensation. This optical flow equation shows that the sumof (i) the time derivative of the luma value, (ii) the product of thehorizontal velocity and the horizontal component of the spatial gradientof a reference picture, and (iii) the product of the vertical velocityand the vertical component of the spatial gradient of a referencepicture is equal to zero. A motion vector of each block obtained from,for example, a merge list is corrected pixel by pixel based on acombination of the optical flow equation and Hermite interpolation.

Note that a motion vector may be derived on the decoder side using amethod other than deriving a motion vector based on a model assuminguniform linear motion. For example, a motion vector may be derived foreach sub-block based on motion vectors of neighboring blocks.

Here, a mode in which a motion vector is derived for each sub-blockbased on motion vectors of neighboring blocks will be described. Thismode is also referred to as affine motion compensation prediction mode.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks. In FIG. 9A, the currentblock includes 16 4×4 sub-blocks. Here, motion vector v₀ of the top leftcorner control point in the current block is derived based on motionvectors of neighboring sub-blocks, and motion vector v₁ of the top rightcorner control point in the current block is derived based on motionvectors of neighboring blocks. Then, using the two motion vectors v₀ andv₁, the motion vector (v_(x), v_(y)) of each sub-block in the currentblock is derived using Equation 2 below.

$\begin{matrix}{{MATH}.\mspace{14mu} 2} & \; \\\{ \begin{matrix}{v_{x} = {{\frac{( {v_{1x} - v_{0x}} )}{w}x} - {\frac{( {v_{1y} - v_{0y}} )}{w}y} + v_{0x}}} \\{v_{y} = {{\frac{( {v_{1y} - v_{0y}} )}{w}x} + {\frac{( {v_{1x} - v_{0x}} )}{w}y} + v_{0y}}}\end{matrix}  & (2)\end{matrix}$

Here, x and y are the horizontal and vertical positions of thesub-block, respectively, and w is a predetermined weighted coefficient.

Such an affine motion compensation prediction mode may include a numberof modes of different methods of deriving the motion vectors of the topleft and top right corner control points. Information indicating such anaffine motion compensation prediction mode (referred to as, for example,an affine flag) is signalled at the CU level. Note that the signaling ofinformation indicating the affine motion compensation prediction modeneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, CTU level, or sub-block level).

[Prediction Controller]

Prediction controller 128 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto subtractor 104 and adder 116.

Here, an example of deriving a motion vector via merge mode in a currentpicture will be given. FIG. 9B is for illustrating an outline of aprocess for deriving a motion vector via merge mode.

First, an MV predictor list in which candidate MV predictors areregistered is generated. Examples of candidate MV predictors include:spatially neighboring MV predictors, which are MVs of encoded blockspositioned in the spatial vicinity of the current block; a temporallyneighboring MV predictor, which is an MV of a block in an encodedreference picture that neighbors a block in the same location as thecurrent block; a combined MV predictor, which is an MV generated bycombining the MV values of the spatially neighboring MV predictor andthe temporally neighboring MV predictor; and a zero MV predictor, whichis an MV whose value is zero.

Next, the MV of the current block is determined by selecting one MVpredictor from among the plurality of MV predictors registered in the MVpredictor list.

Furthermore, in the variable-length encoder, a merge_idx, which is asignal indicating which MV predictor is selected, is written and encodedinto the stream.

Note that the MV predictors registered in the MV predictor listillustrated in FIG. 9B constitute one example. The number of MVpredictors registered in the MV predictor list may be different from thenumber illustrated in FIG. 9B, the MV predictors registered in the MVpredictor list may omit one or more of the types of MV predictors givenin the example in FIG. 9B, and the MV predictors registered in the MVpredictor list may include one or more types of MV predictors inaddition to and different from the types given in the example in FIG.9B.

Note that the final MV may be determined by performing DMVR processing(to be described later) by using the MV of the current block derived viamerge mode.

Here, an example of determining an MV by using DMVR processing will begiven.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

First, the most appropriate MVP set for the current block is consideredto be the candidate MV, reference pixels are obtained from a firstreference picture, which is a picture processed in the L0 direction inaccordance with the candidate MV, and a second reference picture, whichis a picture processed in the L1 direction in accordance with thecandidate MV, and a template is generated by calculating the average ofthe reference pixels.

Next, using the template, the surrounding regions of the candidate MVsof the first and second reference pictures are searched, and the MV withthe lowest cost is determined to be the final MV. Note that the costvalue is calculated using, for example, the difference between eachpixel value in the template and each pixel value in the regionssearched, as well as the MV value.

Note that the outlines of the processes described here are fundamentallythe same in both the encoder and the decoder.

Note that processing other than the processing exactly as describedabove may be used, so long as the processing is capable of deriving thefinal MV by searching the surroundings of the candidate MV.

Here, an example of a mode that generates a prediction image by usingLIC processing will be given.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

First, an MV is extracted for obtaining, from an encoded referencepicture, a reference image corresponding to the current block.

Next, information indicating how the luminance value changed between thereference picture and the current picture is extracted and a luminancecorrection parameter is calculated by using the luminance pixel valuesfor the encoded left neighboring reference region and the encoded upperneighboring reference region, and the luminance pixel value in the samelocation in the reference picture specified by the MV.

The prediction image for the current block is generated by performing aluminance correction process by using the luminance correction parameteron the reference image in the reference picture specified by the MV.

Note that the shape of the surrounding reference region illustrated inFIG. 9D is just one example; the surrounding reference region may have adifferent shape.

Moreover, although a prediction image is generated from a singlereference picture in this example, in cases in which a prediction imageis generated from a plurality of reference pictures as well, theprediction image is generated after performing a luminance correctionprocess, via the same method, on the reference images obtained from thereference pictures.

One example of a method for determining whether to implement LICprocessing is by using an lic_flag, which is a signal that indicateswhether to implement LIC processing. As one specific example, theencoder determines whether the current block belongs to a region ofluminance change. The encoder sets the lic_flag to a value of “1” whenthe block belongs to a region of luminance change and implements LICprocessing when encoding, and sets the lic_flag to a value of “0” whenthe block does not belong to a region of luminance change and encodeswithout implementing LIC processing. The decoder switches betweenimplementing LIC processing or not by decoding the lic_flag written inthe stream and performing the decoding in accordance with the flagvalue.

One example of a different method of determining whether to implementLIC processing is determining so in accordance with whether LICprocessing was determined to be implemented for a surrounding block. Inone specific example, when merge mode is used on the current block,whether LIC processing was applied in the encoding of the surroundingencoded block selected upon deriving the MV in the merge mode processingmay be determined, and whether to implement LIC processing or not can beswitched based on the result of the determination. Note that in thisexample, the same applies to the processing performed on the decoderside.

[Decoder Outline]

Next, a decoder capable of decoding an encoded signal (encodedbitstream) output from encoder 100 will be described. FIG. 10 is a blockdiagram illustrating a functional configuration of decoder 200 accordingto Embodiment 1. Decoder 200 is a moving picture/picture decoder thatdecodes a moving picture/picture block by block.

As illustrated in FIG. 10, decoder 200 includes entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, block memory210, loop filter 212, frame memory 214, intra predictor 216, interpredictor 218, and prediction controller 220.

Decoder 200 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, loop filter212, intra predictor 216, inter predictor 218, and prediction controller220. Alternatively, decoder 200 may be realized as one or more dedicatedelectronic circuits corresponding to entropy decoder 202, inversequantizer 204, inverse transformer 206, adder 208, loop filter 212,intra predictor 216, inter predictor 218, and prediction controller 220.

Hereinafter, each component included in decoder 200 will be described.

[Entropy Decoder]

Entropy decoder 202 entropy decodes an encoded bitstream. Morespecifically, for example, entropy decoder 202 arithmetic decodes anencoded bitstream into a binary signal. Entropy decoder 202 thendebinarizes the binary signal. With this, entropy decoder 202 outputsquantized coefficients of each block to inverse quantizer 204.

[Inverse Quantizer]

Inverse quantizer 204 inverse quantizes quantized coefficients of ablock to be decoded (hereinafter referred to as a current block), whichare inputs from entropy decoder 202. More specifically, inversequantizer 204 inverse quantizes quantized coefficients of the currentblock based on quantization parameters corresponding to the quantizedcoefficients. Inverse quantizer 204 then outputs the inverse quantizedcoefficients (i.e., transform coefficients) of the current block toinverse transformer 206.

[Inverse Transformer]

Inverse transformer 206 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 204.

For example, when information parsed from an encoded bitstream indicatesapplication of EMT or AMT (for example, when the AMT flag is set totrue), inverse transformer 206 inverse transforms the transformcoefficients of the current block based on information indicating theparsed transform type.

Moreover, for example, when information parsed from an encoded bitstreamindicates application of NSST, inverse transformer 206 applies asecondary inverse transform to the transform coefficients.

[Adder]

Adder 208 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 206, and prediction samples,which is an input from prediction controller 220. Adder 208 then outputsthe reconstructed block to block memory 210 and loop filter 212.

[Block Memory]

Block memory 210 is storage for storing blocks in a picture to bedecoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 210 storesreconstructed blocks output from adder 208.

[Loop Filter]

Loop filter 212 applies a loop filter to blocks reconstructed by adder208, and outputs the filtered reconstructed blocks to frame memory 214and, for example, a display device.

When information indicating the enabling or disabling of ALF parsed froman encoded bitstream indicates enabled, one filter from among aplurality of filters is selected based on direction and activity oflocal gradients, and the selected filter is applied to the reconstructedblock.

[Frame Memory]

Frame memory 214 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 214 stores reconstructed blocks filtered byloop filter 212.

[Intra Predictor]

Intra predictor 216 generates a prediction signal (intra predictionsignal) by intra prediction with reference to a block or blocks in thecurrent picture and stored in block memory 210. More specifically, intrapredictor 216 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 220.

Note that when an intra prediction mode in which a chroma block is intrapredicted from a luma block is selected, intra predictor 216 may predictthe chroma component of the current block based on the luma component ofthe current block.

Moreover, when information indicating the application of PDPC is parsedfrom an encoded bitstream, intra predictor 216 correctspost-intra-prediction pixel values based on horizontal/verticalreference pixel gradients.

[Inter Predictor]

Inter predictor 218 predicts the current block with reference to areference picture stored in frame memory 214. Inter prediction isperformed per current block or per sub-block (for example, per 4×4block) in the current block. For example, inter predictor 218 generatesan inter prediction signal of the current block or sub-block by motioncompensation by using motion information (for example, a motion vector)parsed from an encoded bitstream, and outputs the inter predictionsignal to prediction controller 220.

Note that when the information parsed from the encoded bitstreamindicates application of OBMC mode, inter predictor 218 generates theinter prediction signal using motion information for a neighboring blockin addition to motion information for the current block obtained frommotion estimation.

Moreover, when the information parsed from the encoded bitstreamindicates application of FRUC mode, inter predictor 218 derives motioninformation by performing motion estimation in accordance with thepattern matching method (bilateral matching or template matching) parsedfrom the encoded bitstream. Inter predictor 218 then performs motioncompensation using the derived motion information.

Moreover, when BIO mode is to be applied, inter predictor 218 derives amotion vector based on a model assuming uniform linear motion. Moreover,when the information parsed from the encoded bitstream indicates thataffine motion compensation prediction mode is to be applied, interpredictor 218 derives a motion vector of each sub-block based on motionvectors of neighboring blocks.

[Prediction Controller]

Prediction controller 220 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto adder 208.

[Adaptive Loop Filter]

The following describes adaptive loop filter (ALF) processing performedby loop filter 120. FIG. 12 is a block diagram illustrating an exampleof a configuration of loop filter 120 according to the presentembodiment. FIG. 13 is a flowchart of filter processing by loop filter120.

Loop filter 120 generates filtered image 316 by performing filterprocessing on reconstructed image 311. Reconstructed image 311 is aninput image for filter processing, and is a decoded image after beingsubjected to inverse orthogonal transform. Note that reconstructed image311 may be an image which has been subjected to another filterprocessing such as deblocking filtering (DF) or sample adaptive offset(SAO). Alternatively, the other filter processing mentioned above may beperformed on an image which has been subjected to ALF processing.

Loop filter 120 includes edge intensity calculator 301, edge intensitydeterminer 302, clip processor 303, filter processor 304, and selector305.

Edge intensity calculator 301 calculates unclipped edge intensities 312of blocks included in reconstructed image 311 (S101). Here, a block is aprocessing unit of filter processing and is constituted by n×n pixels(for example, n=2 or 4).

The following processing of steps S102 to S104 is repeatedly performedfor each block. Edge intensity determiner 302 compares unclipped edgeintensity 312 of a current block with threshold 313 for unclipped edgeintensities (S102). When unclipped edge intensity 312 is greater than orequal to threshold 313 (Yes in S102), filter processor 304 skips filterprocessing (ALF processing) on the current block (S103). Specifically,selector 305 outputs reconstructed image 311 as filtered image 316.

On the other hand, when unclipped edge intensity 312 is lower thanthreshold 313 (No in S102), filter processor 304 performs filterprocessing (ALF processing) on the current block (S104). Specifically,clip processor 303 calculates clipped edge intensity 314 by performingclip processing on unclipped edge intensity 312. For example, clipprocessor 303 outputs, as clipped edge intensity 314, unclipped edgeintensity 312 as it is when unclipped edge intensity 312 is lower thanor equal to a predetermined value (for example, 15). When unclipped edgeintensity 312 exceeds the predetermined value (for example, 15), clipprocessor 303 outputs the predetermined value (for example, 15) asclipped edge intensity 314.

Next, filter processor 304 generates filtered image 315 by performingfilter processing according to clipped edge intensity 314 onreconstructed image 311 of the current block. Selector 305 outputsgenerated filtered image 315 as filtered image 316. For example, filterprocessor 304 performs ALF processing disclosed in PTL 2.

Note that when filter processing is skipped (S103), loop filter 120 mayseparately perform dedicated filter processing on reconstructed image311, and output the resultant image as filtered image 316, rather thanoutputting reconstructed image 311 as it is as filtered image 316.

Threshold 313 may be a predetermined fixed value or may be a valueexternally determined. Alternatively, loop filter 120 may calculate avalue of threshold 313 that makes the residual, which is the differencebetween filtered image 316 and an original image, smallest in aprocessing unit such as a picture, and may set threshold 313 to thevalue.

Further, loop filter 120 may set the value of threshold 313 to a valuegreater than the maximum value of unclipped edge intensity 312.Accordingly, unclipped edge intensity 312 is lower than threshold 313 atall times (No in S102), and thus filter processing is performed at alltimes (S104). Thus, when filter processing is to be performed at alltimes, loop filter 120 sets the value of threshold 313 to a valuegreater than the maximum value of unclipped edge intensity 312.

In ALF processing, a filter coefficient, for instance, is determined perprocessing unit (for example, CU, CTU, slice, picture, or sequence) thatincludes a plurality of blocks so that the residual after filterprocessing is the smallest. In this case, filter processor 304 mayselect a pixel to which a filter is to be applied, based on threshold313, and design a filter coefficient for the selected pixel.Specifically, filter processor 304 may determine a filter coefficient,for instance, which makes the residual the smallest, using blocks whoseunclipped edge intensity 312 is lower than threshold 313 and whichremain after excluding blocks whose unclipped edge intensity 312 isthreshold 313 or higher from blocks included in a processing unit. Inother words, filter processor 304 may determine a filter coefficient,for instance, which makes the residual the smallest, using blocks whichare to be subjected to filter processing and remain after excludingblocks which are not to be subjected to filter processing from blocksincluded in a processing unit.

Note that here, operation of loop filter 120 included in encoder 100 hasbeen described, yet loop filter 212 included in decoder 200 performssimilar operation.

The following describes a technique in the ALF as an example of atechnique of calculating unclipped edge intensity 312 of the currentblock. Note that calculation of edge intensities is not limited to thistechnique, and edge intensities for a predetermined direction such as ahorizontal or vertical direction may be calculated by filter processing,for instance.

When a block includes 4×4 pixels, edge intensity calculator 301calculates unclipped edge intensity 312 for each block having 4×4pixels. Edge intensity calculator 301 first applies a filter having 3taps in each of the horizontal direction and the vertical direction to afiltering target input image (reconstructed image 311), as indicated by(Expression 1) and (Expression 2). Next, edge intensity calculator 301obtains TempHV by adding the results of the expressions, as indicated by(Expression 3).TempH[x][y]=abs((s[x][y]<<1)−(s[x−1][y])−(s[x+1][y]))   (Expression 1)TempV[x][y]=abs((s[x][y]<<1)−(s[x][y−1])−(s[x][y+1]))   (Expression 2)TempHV[x][y]−TempH[x][y]+TempV[x][y]  (Expression 3)(x=1˜width−1,y=1˜height−1,x++,y++,s[ ][ ]: filtering target input image)

Then, edge intensity calculator 301 applies a filter having 6 taps inthe horizontal direction to TempHV for each 4-pixel unit, as indicatedby (Expression 4). Next, edge intensity calculator 301 applies a filterhaving 6 taps in the vertical direction to the result for each 4-pixelunit, as indicated by (Expression 5). Accordingly, unclipped edgeintensity 312 is calculated for each 4×4 pixel unit.

$\begin{matrix}{{{{TempHV}^{\prime}\lbrack x\rbrack}\lbrack y\rbrack} = {{( {{{{TempHV}\lbrack {x - 1} \rbrack}\lbrack y\rbrack} + {{{TempHV}\lbrack {x + 4} \rbrack}\lbrack y\rbrack}} )*1} + {( {{{{TempHV}\lbrack {x + 0} \rbrack}\lbrack y\rbrack} + {{{TempHV}\lbrack {x + 3} \rbrack}\lbrack y\rbrack}} )*2} + {( {{{{TempHV}\lbrack {x + 1} \rbrack}\lbrack y\rbrack} + {{{TempHV}\lbrack {x + 2} \rbrack}\lbrack y\rbrack}} )*3}}} & ( {{Expression}\mspace{14mu} 4} ) \\{( {{y = {0 \sim {{height} - 1}}};{y++}} ),{{( {{x = {1 \sim {{width} - 1}}};{x+=4}} ){{{TempHV}^{''}\lbrack {x - 1} \rbrack}\lbrack {y - 1} \rbrack}} = {{( {{{{TempHV}^{\prime}\lbrack x\rbrack}\lbrack {y - 1} \rbrack} + {{{TempHV}\lbrack x\rbrack}\lbrack {y + 4} \rbrack}} )*1} + {( {{{{TempHV}^{\prime}\lbrack x\rbrack}\lbrack {y + 0} \rbrack} + {{{TempHV}\lbrack x\rbrack}\lbrack {y + 3} \rbrack}} )*2} + {( {{{{TempHV}^{\prime}\lbrack x\rbrack}\lbrack {y + 1} \rbrack} + {{{TempHV}\lbrack x\rbrack}\lbrack {y + 2} \rbrack}} )*3}}}} & ( {{Expression}\mspace{14mu} 5} )\end{matrix}$(y=1˜height−1;y+=4), (x=1˜width−1;x+=4)

The following describes a specific example of determination processing.FIG. 14A illustrates an example of reconstructed image 311. FIG. 14Billustrates examples of unclipped edge intensities 312. FIG. 14Cillustrates examples of determination results 317 of determining whetherfilter processing is ON or OFF.

Reconstructed image 311 illustrated in FIG. 14A shows the highestluminance values of 4×4 pixel units. Unclipped edge intensities 312illustrated in FIG. 14B are output by edge intensity calculator 301 andindicate edge intensities for 4×4 pixel units. Determination results 317illustrated in FIG. 14C are output by edge intensity determiner 302, andindicate, for each of 4×4 pixel units, whether filter processing is tobe performed.

In a region in which the luminance value abruptly changes inreconstructed image 311, the values of unclipped edge intensities 312are also large values that are greater than 30 as illustrated in FIG.14B. For example, when the value of threshold 313 is “30”, edgeintensity determiner 302 determines that filter processing is not to beperformed (OFF) on a region whose unclipped edge intensity 312 isgreater than or equal to “30”, and determines that filter processing isto be performed (ON) on a region whose unclipped edge intensity 312 islower than “30”. Consequently, as illustrated in FIG. 14C, filterprocessing is not performed on a region in which the luminance valueabruptly changes, and filter processing is performed on the otherregion.

Note that the above has described an example of performing ALF as filterprocessing, yet a similar technique may be applied also to anotherfilter processing. For example, this filter processing may be applied toall the pixels in a block, as in the case of ALF.

As described above, encoder 100 according to the present embodimentgenerates reconstructed image 311 by subjecting an original image toencoding (subtraction of a prediction signal, orthogonal transform, andquantization) and decoding (inverse quantization, inverse orthogonaltransform, and addition of a prediction signal). When the edge intensityof a current block included in reconstructed image 311 is lower thanthreshold 313, encoder 100 performs, on the current block, filterprocessing that is applied to all the pixels in the current block. Whenunclipped edge intensity 312 of the current block is higher thanthreshold 313, encoder 100 skips the above filter processing on thecurrent block.

Accordingly, encoder 100 skips filter processing on a block having ahigh edge intensity. Accordingly, for example, filter processing can beprevented from being performed on a block which may be greatly differentfrom an original image due to being subjected to filter processing.Accordingly, the quality of filtered image 316 can be improved.

For example, the above filter processing is ALF processing.Specifically, filters to be used are associated with a plurality ofgroups (classes) that are ranges of edge intensities. Specifically, thegroups are successive ranges of edge intensities that do not overlapeach other. For example, encoder 100 determines, for each group, afilter which makes the residual between an original image and filteredimage 315 the smallest.

Encoder 100 determines a group that includes the edge intensity of thecurrent block from among the groups. Encoder 100 uses a filterassociated with the group determined to include the edge intensity ofthe current block.

Encoder 100 calculates clipped edge intensity 314 by clipping unclippededge intensity 312 to a predetermined value (for example, 15). The groupin filter processing is determined based on clipped edge intensity 314,and whether filter processing is to be performed is determined based onunclipped edge intensity 312. Specifically, encoder 100 determines agroup that includes clipped edge intensity 314. When unclipped edgeintensity 312 is lower than threshold 313, encoder 100 performs filterprocessing on the current block, whereas when unclipped edge intensity312 is higher than threshold 313, encoder 100 does not perform filterprocessing on the current block.

Threshold 313 is higher than the predetermined value (for example, 15).Alternatively, threshold 313 is higher than the smallest value of edgeintensities in a group that is the highest range of edge intensitiesamong the groups. Stated differently, threshold 313 is included in agroup that is the highest range of edge intensities among the groups.

As described above, encoder 100 determines whether to perform filterprocessing, by comparing unclipped edge intensity 312 with threshold 313higher than the predetermined value (for example, 15). Accordingly,encoder 100 can determine a block having a particularly high edgeintensity among blocks having edge intensities that are higher than thepredetermined value and are determined to be in the same group.Accordingly, filter processing can be prevented from being performed ona block on which filter processing may exert a bad influence.

Decoder 200 also performs similar processing. Specifically, decoder 200generates reconstructed image 311 by decoding encoded data (entropydecoding, inverse quantization, inverse transform, and addition of aprediction signal). When the edge intensity of a current block includedin reconstructed image 311 is lower than threshold 313, decoder 200performs, on the current block, filter processing that is applied to allthe pixels in the current block. Decoder 200 skips filter processing onthe current block, when unclipped edge intensity 312 of the currentblock is higher than threshold 313.

Embodiment 2

The present embodiment describes a variation of loop filter 120. FIG. 15is a block diagram illustrating an example of a configuration of loopfilter 120A according to the present embodiment. FIG. 16 is a flowchartof filter processing by loop filter 120A.

Loop filter 120A according to the present embodiment is different fromloop filter 120 according to Embodiment 1 in that loop filter 120Adynamically determines threshold 313.

As illustrated in FIG. 15, loop filter 120A includes thresholddeterminer 306, in addition to the configuration of loop filter 120.Encoder 100 includes threshold encoder 307. The processing illustratedin FIG. 16 results from adding steps S105 and S106 to the processingillustrated in FIG. 13.

Threshold determiner 306 determines threshold 313 (S105). For example,the determination of threshold 313 is carried out as pre-processing offilter processing, for each processing unit such as CU, CTU, slice,picture, or sequence. For example, on the assumption that filterprocessing is not performed on a block whose unclipped edge intensity312 is threshold 313 or higher, threshold determiner 306 calculatesthreshold 313 that makes the residual, which is the difference betweenfiltered image 316 and an original image, the smallest.

At this time, threshold determiner 306 sets the maximum value ofthreshold 313 to a value obtained by adding 1 to the greatest value ofunclipped edge intensities 312 of blocks in a processing unit (forexample, slice). The maximum value is a value for determining thatfilter processing is to be performed on all the blocks in the processingunit. In addition, threshold determiner 306 sets the minimum value ofthreshold 313 to the smallest value of unclipped edge intensities 312 ofthe blocks in the processing unit. The minimum value is a value fordetermining that filter processing is not to be performed on all theblocks in the processing unit. Threshold determiner 306 calculates aresidual, changing the value of threshold 313 in a range from the setminimum value to the set maximum value, and determines the value ofthreshold 313 that makes the residual the smallest, as the value ofthreshold 313 to be used.

Threshold encoder 307 encodes information that indicates determinedthreshold 313 (S106). Specifically, threshold encoder 307 generates anencoded bitstream that includes the above information, by signaling theabove information in an encoded bitstream. For example, the aboveinformation is stored in header information (CU header, CTU header,slice header, PPS, or SPS) for each CU, CTU, slice, picture, orsequence. Threshold encoder 307 is included in entropy encoder 110illustrated in FIG. 1, for example.

As described above, encoder 100 according to the present embodiment candetermine appropriate threshold 313 according to an input image, andthus can appropriately determine whether filter processing is to beperformed, using appropriate threshold 313.

Embodiment 3

The present embodiment describes a variation of loop filter 120Aaccording to Embodiment 2. FIG. 17 is a block diagram illustrating anexample of a configuration of loop filter 120B according to the presentembodiment. FIG. 18 is a flowchart of filter processing by loop filter120B.

Loop filter 120B illustrated in FIG. 17 includes statistic calculator308, in addition to the configuration of loop filter 120A illustrated inFIG. 15. Edge intensity determiner 302A has additional functions. Theprocessing illustrated in FIG. 18 results from adding steps S107, S108,and S109 to the processing illustrated in FIG. 16.

Based on the edge intensities of blocks included in a processing unit,statistic calculator 308 calculates statistic 318 of the edgeintensities for the processing unit (S107). For example, statisticcalculator 308 calculates statistic 318 for each processing unit such asCU, CTU, slice, picture, or sequence, as the pre-processing of filterprocessing. Specifically, statistic calculator 308 calculates statistic318 of unclipped edge intensities 312 of blocks included in a processingunit which is to be subjected to filter processing.

For example, statistic 318 is the percentage of blocks whose unclippededge intensities 312 are 0, among blocks included in a processing unit.Note that statistic 318 may indicate the percentage of blocks whoseunclipped edge intensities 312 are lower or higher than a predeterminedvalue, among blocks included in a processing unit, or may be an averageor a standard deviation of unclipped edge intensities 312 of blocks.

Edge intensity determiner 302A determines whether statistic 318satisfies a predetermined condition (S108). When statistic 318 satisfiesthe predetermined condition (Yes in S108), edge intensity determiner302A determines that filter processing is to be performed on all theblocks included in a processing unit. Then, filter processor 304performs filter processing on all the blocks included in the processingunit (S109).

Here, the above condition is that statistic 318 is greater than or equalto a predetermined threshold when statistic 318 indicates the percentageof blocks whose unclipped edge intensities 312 are zero, or thepercentage of blocks whose unclipped edge intensities 312 are lower thana predetermined value. When statistic 318 indicates the percentage ofblocks whose unclipped edge intensities 312 are higher than apredetermined value, the above condition is that statistic 318 issmaller than the predetermined threshold. When statistic 318 is anaverage or a standard deviation of unclipped edge intensities 312 ofblocks, the above condition is that statistic 318 is smaller than thepredetermined threshold. Note that the condition may be a combination oftwo or more of such conditions.

According to this, encoder 100 can switch whether or not to performdetermination processing of determining whether filter processing is tobe performed, based on statistic 318. Specifically, encoder 100 can skipprocessing from steps S105 to S106, based on statistic 318, when a smallnumber of blocks have high edge intensities or there is a lowpossibility that high edge intensities are distributed widely.Accordingly, the amount of processing can be reduced.

Embodiment 4

The present embodiment describes a variation of loop filter 120according to Embodiment 1. FIG. 19 is a block diagram illustrating anexample of a configuration of loop filter 120C according to the presentembodiment. FIG. 20 is a flowchart of filter processing by loop filter120C.

Loop filter 120C illustrated in FIG. 19 includes group determiner 309,in addition to the configuration of loop filter 120 illustrated in FIG.12. Furthermore, the processing illustrated in FIG. 20 results fromadding step S110 to the processing illustrated in the processing in FIG.13.

Group determiner 309 dynamically determines groups 320 of the edgeintensities in ALF, based on an electro-optical transfer function (EOTF)of a video (an original image or a reconstructed image) indicated byEOTF information 319 (S110). Here, an EOTF is a model which defines thecorrespondence of an actual luminance value and a pixel value (codevalue).

For example, group determiner 309 performs step S110 for each unit forwhich EOTF information 319 may change. Filter processor 304 performsfilter processing on reconstructed image 311, using groups 320, thusgenerating filtered image 315. For example, in ALF, clip processor 303first clips unclipped edge intensity 312 to a value of 0 to 15. Filterprocessor 304 classifies the value of clipped edge intensity 314 intofive-level fixed groups, and applies, to a current block, a filter for agroup into which the value is classified, among filters havingfive-level strengths. In the present embodiment, loop filter 120Cdynamically changes groups 320 for edge intensities, based on EOTFinformation 319, thus dynamically changing the ranges for applyingfilters having five-level strengths.

For example, in HEVC, EOTF information 319 is stored in headerinformation for each sequence, called an SPS (sequence parameter set).Accordingly, group determiner 309 performs the processing in step S110for each sequence. Note that when an HDR video or an SDR video is fixedfor each content, or in other words, when EOTF information 319 is fixedfor each content, group determiner 309 performs processing in step S110once when playback of the content starts.

For example, different EOTFs are used for an HDR video and an SDR video.Furthermore, also in an HDR video, different EOTFs are used in aplurality of methods such as SMPTE ST2084 and ARIB STD B67.

Here, determining groups 320 is to determine ranges of edge intensitiesin a plurality of groups. In other words, to which groups the values ofedge intensities are allocated are changed. For example, when EOTFinformation 319 indicates an EOTF for an HDR video, group determiner 309determines groups 320 so that the group for a range of high edgeintensifies is narrower as compared to the case where EOTF information319 indicates an EOTF for an SDR video. Accordingly, loop filter 120Ccan perform appropriate filter processing also on an HDR video in whichhigh edge intensities tend to appear.

Furthermore, group determiner 309 may determine groups 320, based onstatistic 318 of unclipped edge intensities 312 described in Embodiment3 (such as a percentage of blocks having edge intensities higher orlower than a predetermined value, or an average or a standard deviationof the edge intensities), so that the percentage of pixels included ineach group is greater than or equal to a predetermined value or therange of edge intensities included in each group is a predeterminedvalue or less.

For example, group determiner 309 determines groups 320 so that thegroup for a range of high edge intensities is narrower when a percentageof blocks having edge intensities higher than a predetermined value, oran average or a standard deviation of the edge intensities is high orwhen a percentage of blocks having edge intensities lower than apredetermined value is low. On the contrary, group determiner 309determines groups 320 so that the group for a range of low edgeintensities is narrower when a percentage of blocks having edgeintensities higher than a predetermined value, or an average or astandard deviation of the edge intensities is low or when a percentageof blocks having edge intensities lower than a predetermined value ishigh. Accordingly, this prevents the imbalance of the percentages ofpixels in the groups or the ranges of edge intensities in the groups.

Loop filter 120C may switch, based on an EOTF, whether or not to performdetermination processing (S102 to S104) of determining whether filterprocessing is to be performed. For example, loop filter 120C mayperform, for each block, determination processing (S102 to S104) ofdetermining whether filter processing is to be performed when an EOTFfor an HDR video is used, and may perform filter processing on all theblocks without performing the determination processing (S102 to S104)when an EOTF for an SDR video is used. Accordingly, loop filter 120C caninhibit deterioration of image quality by switching, for each block,whether or not filter processing is to be performed on an HDR video inwhich high edge intensities tend to appear, and furthermore, can reducethe amount of processing in an SDR video.

Loop filter 120C may determine threshold 313, based on an EOTF. Forexample, when an EOTF for an HDR video is used, loop filter 120C maymake threshold 313 lower than the threshold in the case where an EOTFfor an SDR video is used. Accordingly, loop filter 120C can furtherprevent filter processing from being performed on an HDR video in whichhigh edge intensities tend to appear, and thus can inhibit deteriorationof image quality of an HDR video.

The above has given a description of an example in which loop filter120C determines groups 320 according to EOTF information 319, yet loopfilter 120C may determine groups 320 according to the luminance dynamicrange (HDR or SDR) of an original image or a reconstructed image.

Loop filter 120C may dynamically change other parameters for filterprocessing according to, for instance, an EOTF, rather than groups 320in ALF. For example, loop filter 120C may dynamically change the rangeof usable filter coefficients, or the shape of a filter (for example,the number of taps), for instance.

As described above, group determiner 309 determines a parameter for acurrent block included in reconstructed image 311 for filter processingto be applied to all the pixels in the current block, based on an EOTFof an original image or reconstructed image 311. For example, theparameter is according to groups 320.

Filter processor 304 performs filter processing on the current block,using the determined parameter.

Accordingly, encoder 100 can perform filter processing suitable for eachof sequences in which distributions of edge intensities are different(for example, an HDR video and an SDR video). Accordingly, the qualityof decoded images (reconstructed images) can be improved.

Note that here, operation of loop filter 120C included in encoder 100 isdescribed, yet similar operation is performed also in loop filter 212included in decoder 200.

Embodiment 5

The present embodiment describes decoder 200 which decodes an encodedbitstream generated by encoder 100 according to Embodiment 2. FIG. 21 isa block diagram illustrating an example of a configuration of loopfilter 212A according to the present embodiment. FIG. 22 is a flowchartof filter processing by loop filter 212A.

As illustrated in FIG. 21, loop filter 212A differs from loop filter120A illustrated in FIG. 15, in that threshold determiner 306 is notincluded. Decoder 200 includes threshold decoder 321 instead ofthreshold encoder 307. The processing illustrated in FIG. 22 is theprocessing illustrated in FIG. 16 that includes step S111, instead ofsteps S105 and S106.

Threshold decoder 321 decodes information indicating threshold 313 froman encoded bitstream transmitted from encoder 100 (S111). Edge intensitydeterminer 302 determines whether to perform filter processing bycomparing threshold 313 indicated by the decoded information, andunclipped edge intensity 312 (S102). Threshold decoder 321 is includedin entropy decoder 202 illustrated in FIG. 10, for example.

Embodiment 6

The present embodiment describes decoder 200 which decodes an encodedbitstream generated by encoder 100 according to Embodiment 3. FIG. 23 isa block diagram illustrating an example of a configuration of loopfilter 212B according to the present embodiment. FIG. 24 is a flowchartof filter processing by loop filter 212B.

As illustrated in FIG. 23, loop filter 212B differs from loop filter120B illustrated in FIG. 17 in that threshold determiner 306 is notincluded. Decoder 200 includes threshold decoder 321 instead ofthreshold encoder 307. Processing illustrated in FIG. 24 is theprocessing illustrated in FIG. 18 that includes step S111, instead ofsteps S105 and S106.

Threshold decoder 321 decodes information indicating threshold 313 froman encoded bitstream transmitted by encoder 100 (S111). Edge intensitydeterminer 302 determines whether to perform filter processing bycomparing threshold 313 indicated by the decoded information, andunclipped edge intensity 312 (S102).

[Example of Implementation of Encoder]

FIG. 25 is a block diagram illustrating an example of implementation ofencoder 100 according to Embodiments 1 to 6. Encoder 100 includescircuitry 160 and memory 162. For example, plural elements of encoder100 illustrated in FIG. 1 are implemented by circuitry 160 and memory162 illustrated in FIG. 20.

Circuitry 160 processes information and is accessible to memory 162. Forexample, circuitry 160 is a dedicated or general-purpose electroniccircuit which encodes image information. Circuitry 160 may be aprocessor like a CPU. Circuitry 160 may be an aggregate of pluralelectronic circuits. For example, circuitry 160 may play the roles ofplural elements of encoder 100 illustrated in FIG. 1 other than theelements for storing information.

Memory 162 is a general purpose or dedicated memory which storesinformation for circuitry 160 to encode image information. Memory 162may be an electronic circuit and may be connected to circuitry 160.Memory 162 may be included in circuitry 160. Memory 162 may be anaggregate of plural electronic circuits. Memory 162 may be a magneticdisk or an optical disc, and may be expressed as storage or a recordingmedium. Memory 162 may be nonvolatile memory or volatile memory.

For example, memory 162 may store image information to be encoded or abit string corresponding to the encoded image information. Memory 162may store a program for circuitry 160 to encode image information.

For example, circuitry 160 may play the roles of elements for storinginformation among the elements of encoder 100 illustrated in FIG. 1.Specifically, memory 162 may play the roles of block memory 118 andframe memory 122 illustrated in FIG. 1.

Note that encoder 100 may not include all the elements illustrated inFIG. 1 or may not perform all the processes described above. Anotherdevice may include one or more of the elements illustrated in, forinstance, FIG. 1, or may perform one or more of the processes describedabove. Encoder 100 includes one or more of the elements illustrated inthe FIG. 1, for instance, and performs one or more of the processesdescribed above, whereby delay of processing can be inhibited.

[Example of Implementation of Decoder]

FIG. 26 is a block diagram illustrating an example of implementation ofdecoder 200 according to Embodiments 1 to 6. Decoder 200 includescircuitry 260 and memory 262. For example, elements of decoder 200illustrated in FIG. 10 are implemented by circuitry 260 and memory 262illustrated in FIG. 21.

Circuitry 260 processes information and is accessible to memory 262. Forexample, circuitry 260 is a general purpose or dedicated electroniccircuit which decodes image information. Circuitry 260 may be aprocessor like a CPU. Circuitry 260 may be an aggregate of pluralelectronic circuits. For example, circuitry 260 may play the roles ofplural elements of decoder 200 illustrated in FIG. 10 other than theelements for storing information.

Memory 262 is a general purpose or dedicated memory that storesinformation for circuitry 260 to decode image information. Memory 262may be an electronic circuit and may be connected to circuitry 260.Memory 262 may be included in circuitry 260. Memory 262 may be anaggregate of plural electronic circuits. Memory 262 may be a magneticdisk or an optical disc, for instance, and may be expressed as storageor a recording medium. Furthermore, memory 262 may be nonvolatile memoryor volatile memory.

For example, memory 262 may store a bit string corresponding to encodedimage information or image information corresponding to a decoded bitstring. Memory 262 may store a program for circuitry 260 to decode imageinformation.

For example, circuitry 260 may play the role of elements for storinginformation among the plural elements of decoder 200 illustrated in FIG.10. Specifically, memory 262 may play the roles of block memory 210 andframe memory 214 illustrated in FIG. 10.

Note that decoder 200 may not include all the elements illustrated inFIG. 10, for instance, and may not perform all the processes mentionedabove. Another device may include one or more of the elementsillustrated in, for instance, FIG. 10, and may perform one or more ofthe processes described above. Decoder 200 includes one or more of theelements illustrated in, for instance, FIG. 10, and perform one or moreof the processes mentioned above, whereby delay of processing may beinhibited.

Although the above has given a description of the encoder and thedecoder according to the present embodiment, the present disclosure isnot limited to the present embodiment.

The processing sections included in the encoder and the decoderaccording to the above embodiments are typically implemented as largescale integrated circuits (LSIs). These may be each formed as a singlechip or may be formed as a single chip that includes some or all of thesections.

Furthermore, the method of circuit integration is not limited to LSIs,and implementation through a dedicated circuit or a general-purposeprocessor is also possible. A field programmable gate array (FPGA) thatallows programming after LSI manufacturing or a reconfigurable processorthat allows reconfiguration of the connections and settings of thecircuit cells inside the LSI may also be used.

In the above embodiments, each of the elements may be constituted bydedicated hardware, or may be obtained by executing a software programsuitable for the element. Each element may be obtained by a programexecutor such as a CPU or a processor reading and executing a softwareprogram stored in a recording medium such as a hard disk orsemiconductor memory.

In other words, the encoder and the decoder each include processingcircuitry and storage electrically connected to the processing circuitry(accessible from the processing circuitry). The processing circuitryincludes at least one of dedicated hardware and a program executor. Whenthe processing circuitry includes the program executor, the storagestores a software program executed by the program executor. Theprocessing circuitry performs the encoding method or the decoding methodaccording to the above embodiment using the storage.

Further, the present disclosure may be the above software program or anon-transitory computer readable recording medium on which the aboveprogram is recorded. It goes without saying that the above program canbe distributed via a transmission medium such as the Internet.

All the numbers used above are examples in order to specificallydescribe the present disclosure, and the present disclosure is notlimited to the exemplified numbers.

The split of the functional blocks in the block diagrams is an example,plural functional blocks may be implemented as one functional block, onefunctional block may be split into a plurality of blocks, or one or moreof the functions may be transferred to another functional block. Similarfunctions of plural functional blocks may be processed in parallel or ina time divisional manner by a single hardware or software.

The orders in which the steps included in the encoding method and thedecoding method are performed are examples in order to specificallydescribe the present disclosure, and may be orders other than the above.One or more of the steps may be performed simultaneously (parallel) withother steps.

The above has given a description of the encoder, the decoder, theencoding method, and the decoding method according to one or moreaspects of the present disclosure, based on the embodiments, yet thepresent disclosure is not limited to the embodiments. The scope of theone or more aspects of the present disclosure also encompassesembodiments as a result of adding, to the embodiments, variousmodifications that may be conceived by those skilled in the art, andembodiments obtained by combining elements in different embodiments, aslong as the resultant embodiments do not depart from the spirit of thepresent disclosure.

Embodiment 7

As described in each of the above embodiments, each functional block cantypically be realized as an MPU and memory, for example. Moreover,processes performed by each of the functional blocks are typicallyrealized by a program execution unit, such as a processor, reading andexecuting software (a program) recorded on a recording medium such asROM. The software may be distributed via, for example, downloading, andmay be recorded on a recording medium such as semiconductor memory anddistributed. Note that each functional block can, of course, also berealized as hardware (dedicated circuit).

Moreover, the processing described in each of the embodiments may berealized via integrated processing using a single apparatus (system),and, alternatively, may be realized via decentralized processing using aplurality of apparatuses. Moreover, the processor that executes theabove-described program may be a single processor or a plurality ofprocessors. In other words, integrated processing may be performed, and,alternatively, decentralized processing may be performed.

Embodiments of the present disclosure are not limited to the aboveexemplary embodiments; various modifications may be made to theexemplary embodiments, the results of which are also included within thescope of the embodiments of the present disclosure.

Next, application examples of the moving picture encoding method (imageencoding method) and the moving picture decoding method (image decodingmethod) described in each of the above embodiments and a system thatemploys the same will be described. The system is characterized asincluding an image encoder that employs the image encoding method, animage decoder that employs the image decoding method, and an imageencoder/decoder that includes both the image encoder and the imagedecoder. Other configurations included in the system may be modified ona case-by-case basis.

[Usage Examples]

FIG. 27 illustrates an overall configuration of content providing systemex100 for implementing a content distribution service. The area in whichthe communication service is provided is divided into cells of desiredsizes, and base stations ex106, ex107, ex108, ex109, and ex110, whichare fixed wireless stations, are located in respective cells.

In content providing system ex100, devices including computer ex111,gaming device ex112, camera ex113, home appliance ex114, and smartphoneex115 are connected to internet ex101 via internet service providerex102 or communications network ex104 and base stations ex106 throughex110. Content providing system ex100 may combine and connect anycombination of the above elements. The devices may be directly orindirectly connected together via a telephone network or near fieldcommunication rather than via base stations ex106 through ex110, whichare fixed wireless stations. Moreover, streaming server ex103 isconnected to devices including computer ex111, gaming device ex112,camera ex113, home appliance ex114, and smartphone ex115 via, forexample, internet ex101. Streaming server ex103 is also connected to,for example, a terminal in a hotspot in airplane ex117 via satelliteex116.

Note that instead of base stations ex106 through ex110, wireless accesspoints or hotspots may be used. Streaming server ex103 may be connectedto communications network ex104 directly instead of via internet ex101or internet service provider ex102, and may be connected to airplaneex117 directly instead of via satellite ex116.

Camera ex113 is a device capable of capturing still images and video,such as a digital camera. Smartphone ex115 is a smartphone device,cellular phone, or personal handyphone system (PHS) phone that canoperate under the mobile communications system standards of the typical2G, 3G, 3.9G, and 4G systems, as well as the next-generation 5G system.

Home appliance ex118 is, for example, a refrigerator or a deviceincluded in a home fuel cell cogeneration system.

In content providing system ex100, a terminal including an image and/orvideo capturing function is capable of, for example, live streaming byconnecting to streaming server ex103 via, for example, base stationex106. When live streaming, a terminal (e.g., computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, orairplane ex117) performs the encoding processing described in the aboveembodiments on still-image or video content captured by a user via theterminal, multiplexes video data obtained via the encoding and audiodata obtained by encoding audio corresponding to the video, andtransmits the obtained data to streaming server ex103. In other words,the terminal functions as the image encoder according to one aspect ofthe present disclosure.

Streaming server ex103 streams transmitted content data to clients thatrequest the stream. Client examples include computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, andterminals inside airplane ex117, which are capable of decoding theabove-described encoded data. Devices that receive the streamed datadecode and reproduce the received data. In other words, the devices eachfunction as the image decoder according to one aspect of the presentdisclosure.

[Decentralized Processing]

Streaming server ex103 may be realized as a plurality of servers orcomputers between which tasks such as the processing, recording, andstreaming of data are divided. For example, streaming server ex103 maybe realized as a content delivery network (CDN) that streams content viaa network connecting multiple edge servers located throughout the world.In a CDN, an edge server physically near the client is dynamicallyassigned to the client. Content is cached and streamed to the edgeserver to reduce load times. In the event of, for example, some kind ofan error or a change in connectivity due to, for example, a spike intraffic, it is possible to stream data stably at high speeds since it ispossible to avoid affected parts of the network by, for example,dividing the processing between a plurality of edge servers or switchingthe streaming duties to a different edge server, and continuingstreaming.

Decentralization is not limited to just the division of processing forstreaming; the encoding of the captured data may be divided between andperformed by the terminals, on the server side, or both. In one example,in typical encoding, the processing is performed in two loops. The firstloop is for detecting how complicated the image is on a frame-by-frameor scene-by-scene basis, or detecting the encoding load. The second loopis for processing that maintains image quality and improves encodingefficiency. For example, it is possible to reduce the processing load ofthe terminals and improve the quality and encoding efficiency of thecontent by having the terminals perform the first loop of the encodingand having the server side that received the content perform the secondloop of the encoding. In such a case, upon receipt of a decodingrequest, it is possible for the encoded data resulting from the firstloop performed by one terminal to be received and reproduced on anotherterminal in approximately real time. This makes it possible to realizesmooth, real-time streaming.

In another example, camera ex113 or the like extracts a feature amountfrom an image, compresses data related to the feature amount asmetadata, and transmits the compressed metadata to a server. Forexample, the server determines the significance of an object based onthe feature amount and changes the quantization accuracy accordingly toperform compression suitable for the meaning of the image. Featureamount data is particularly effective in improving the precision andefficiency of motion vector prediction during the second compressionpass performed by the server. Moreover, encoding that has a relativelylow processing load, such as variable length coding (VLC), may behandled by the terminal, and encoding that has a relatively highprocessing load, such as context-adaptive binary arithmetic coding(CABAC), may be handled by the server.

In yet another example, there are instances in which a plurality ofvideos of approximately the same scene are captured by a plurality ofterminals in, for example, a stadium, shopping mall, or factory. In sucha case, for example, the encoding may be decentralized by dividingprocessing tasks between the plurality of terminals that captured thevideos and, if necessary, other terminals that did not capture thevideos and the server, on a per-unit basis. The units may be, forexample, groups of pictures (GOP), pictures, or tiles resulting fromdividing a picture. This makes it possible to reduce load times andachieve streaming that is closer to real-time.

Moreover, since the videos are of approximately the same scene,management and/or instruction may be carried out by the server so thatthe videos captured by the terminals can be cross-referenced. Moreover,the server may receive encoded data from the terminals, change referencerelationship between items of data or correct or replace picturesthemselves, and then perform the encoding. This makes it possible togenerate a stream with increased quality and efficiency for theindividual items of data.

Moreover, the server may stream video data after performing transcodingto convert the encoding format of the video data. For example, theserver may convert the encoding format from MPEG to VP, and may convertH.264 to H.265.

In this way, encoding can be performed by a terminal or one or moreservers. Accordingly, although the device that performs the encoding isreferred to as a “server” or “terminal” in the following description,some or all of the processes performed by the server may be performed bythe terminal, and likewise some or all of the processes performed by theterminal may be performed by the server. This also applies to decodingprocesses.

[3D, Multi-Angle]

In recent years, usage of images or videos combined from images orvideos of different scenes concurrently captured or the same scenecaptured from different angles by a plurality of terminals such ascamera ex113 and/or smartphone ex115 has increased. Videos captured bythe terminals are combined based on, for example, theseparately-obtained relative positional relationship between theterminals, or regions in a video having matching feature points.

In addition to the encoding of two-dimensional moving pictures, theserver may encode a still image based on scene analysis of a movingpicture either automatically or at a point in time specified by theuser, and transmit the encoded still image to a reception terminal.Furthermore, when the server can obtain the relative positionalrelationship between the video capturing terminals, in addition totwo-dimensional moving pictures, the server can generatethree-dimensional geometry of a scene based on video of the same scenecaptured from different angles. Note that the server may separatelyencode three-dimensional data generated from, for example, a pointcloud, and may, based on a result of recognizing or tracking a person orobject using three-dimensional data, select or reconstruct and generatea video to be transmitted to a reception terminal from videos capturedby a plurality of terminals.

This allows the user to enjoy a scene by freely selecting videoscorresponding to the video capturing terminals, and allows the user toenjoy the content obtained by extracting, from three-dimensional datareconstructed from a plurality of images or videos, a video from aselected viewpoint. Furthermore, similar to with video, sound may berecorded from relatively different angles, and the server may multiplex,with the video, audio from a specific angle or space in accordance withthe video, and transmit the result.

In recent years, content that is a composite of the real world and avirtual world, such as virtual reality (VR) and augmented reality (AR)content, has also become popular. In the case of VR images, the servermay create images from the viewpoints of both the left and right eyesand perform encoding that tolerates reference between the two viewpointimages, such as multi-view coding (MVC), and, alternatively, may encodethe images as separate streams without referencing. When the images aredecoded as separate streams, the streams may be synchronized whenreproduced so as to recreate a virtual three-dimensional space inaccordance with the viewpoint of the user.

In the case of AR images, the server superimposes virtual objectinformation existing in a virtual space onto camera informationrepresenting a real-world space, based on a three-dimensional positionor movement from the perspective of the user. The decoder may obtain orstore virtual object information and three-dimensional data, generatetwo-dimensional images based on movement from the perspective of theuser, and then generate superimposed data by seamlessly connecting theimages. Alternatively, the decoder may transmit, to the server, motionfrom the perspective of the user in addition to a request for virtualobject information, and the server may generate superimposed data basedon three-dimensional data stored in the server in accordance with thereceived motion, and encode and stream the generated superimposed datato the decoder. Note that superimposed data includes, in addition to RGBvalues, an a value indicating transparency, and the server sets the avalue for sections other than the object generated fromthree-dimensional data to, for example, 0, and may perform the encodingwhile those sections are transparent. Alternatively, the server may setthe background to a predetermined RGB value, such as a chroma key, andgenerate data in which areas other than the object are set as thebackground.

Decoding of similarly streamed data may be performed by the client(i.e., the terminals), on the server side, or divided therebetween. Inone example, one terminal may transmit a reception request to a server,the requested content may be received and decoded by another terminal,and a decoded signal may be transmitted to a device having a display. Itis possible to reproduce high image quality data by decentralizingprocessing and appropriately selecting content regardless of theprocessing ability of the communications terminal itself. In yet anotherexample, while a TV, for example, is receiving image data that is largein size, a region of a picture, such as a tile obtained by dividing thepicture, may be decoded and displayed on a personal terminal orterminals of a viewer or viewers of the TV. This makes it possible forthe viewers to share a big-picture view as well as for each viewer tocheck his or her assigned area or inspect a region in further detail upclose.

In the future, both indoors and outdoors, in situations in which aplurality of wireless connections are possible over near, mid, and fardistances, it is expected to be able to seamlessly receive content evenwhen switching to data appropriate for the current connection, using astreaming system standard such as MPEG-DASH. With this, the user canswitch between data in real time while freely selecting a decoder ordisplay apparatus including not only his or her own terminal, but also,for example, displays disposed indoors or outdoors. Moreover, based on,for example, information on the position of the user, decoding can beperformed while switching which terminal handles decoding and whichterminal handles the displaying of content. This makes it possible to,while in route to a destination, display, on the wall of a nearbybuilding in which a device capable of displaying content is embedded oron part of the ground, map information while on the move. Moreover, itis also possible to switch the bit rate of the received data based onthe accessibility to the encoded data on a network, such as when encodeddata is cached on a server quickly accessible from the receptionterminal or when encoded data is copied to an edge server in a contentdelivery service.

[Scalable Encoding]

The switching of content will be described with reference to a scalablestream, illustrated in FIG. 28, that is compression coded viaimplementation of the moving picture encoding method described in theabove embodiments. The server may have a configuration in which contentis switched while making use of the temporal and/or spatial scalabilityof a stream, which is achieved by division into and encoding of layers,as illustrated in FIG. 28. Note that there may be a plurality ofindividual streams that are of the same content but different quality.In other words, by determining which layer to decode up to based oninternal factors, such as the processing ability on the decoder side,and external factors, such as communication bandwidth, the decoder sidecan freely switch between low resolution content and high resolutioncontent while decoding. For example, in a case in which the user wantsto continue watching, at home on a device such as a TV connected to theinternet, a video that he or she had been previously watching onsmartphone ex115 while on the move, the device can simply decode thesame stream up to a different layer, which reduces server side load.

Furthermore, in addition to the configuration described above in whichscalability is achieved as a result of the pictures being encoded perlayer and the enhancement layer is above the base layer, the enhancementlayer may include metadata based on, for example, statisticalinformation on the image, and the decoder side may generate high imagequality content by performing super-resolution imaging on a picture inthe base layer based on the metadata. Super-resolution imaging may beimproving the SN ratio while maintaining resolution and/or increasingresolution. Metadata includes information for identifying a linear or anon-linear filter coefficient used in super-resolution processing, orinformation identifying a parameter value in filter processing, machinelearning, or least squares method used in super-resolution processing.

Alternatively, a configuration in which a picture is divided into, forexample, tiles in accordance with the meaning of, for example, an objectin the image, and on the decoder side, only a partial region is decodedby selecting a tile to decode, is also acceptable. Moreover, by storingan attribute about the object (person, car, ball, etc.) and a positionof the object in the video (coordinates in identical images) asmetadata, the decoder side can identify the position of a desired objectbased on the metadata and determine which tile or tiles include thatobject. For example, as illustrated in FIG. 29, metadata is stored usinga data storage structure different from pixel data such as an SEImessage in HEVC. This metadata indicates, for example, the position,size, or color of the main object.

Moreover, metadata may be stored in units of a plurality of pictures,such as stream, sequence, or random access units. With this, the decoderside can obtain, for example, the time at which a specific personappears in the video, and by fitting that with picture unit information,can identify a picture in which the object is present and the positionof the object in the picture.

[Web Page Optimization]

FIG. 30 illustrates an example of a display screen of a web page on, forexample, computer ex111. FIG. 31 illustrates an example of a displayscreen of a web page on, for example, smartphone ex115. As illustratedin FIG. 30 and FIG. 31, a web page may include a plurality of imagelinks which are links to image content, and the appearance of the webpage differs depending on the device used to view the web page. When aplurality of image links are viewable on the screen, until the userexplicitly selects an image link, or until the image link is in theapproximate center of the screen or the entire image link fits in thescreen, the display apparatus (decoder) displays, as the image links,still images included in the content or I pictures, displays video suchas an animated gif using a plurality of still images or I pictures, forexample, or receives only the base layer and decodes and displays thevideo.

When an image link is selected by the user, the display apparatusdecodes giving the highest priority to the base layer. Note that ifthere is information in the HTML code of the web page indicating thatthe content is scalable, the display apparatus may decode up to theenhancement layer. Moreover, in order to guarantee real timereproduction, before a selection is made or when the bandwidth isseverely limited, the display apparatus can reduce delay between thepoint in time at which the leading picture is decoded and the point intime at which the decoded picture is displayed (that is, the delaybetween the start of the decoding of the content to the displaying ofthe content) by decoding and displaying only forward reference pictures(I picture, P picture, forward reference B picture). Moreover, thedisplay apparatus may purposely ignore the reference relationshipbetween pictures and coarsely decode all B and P pictures as forwardreference pictures, and then perform normal decoding as the number ofpictures received over time increases.

[Autonomous Driving]

When transmitting and receiving still image or video data such two- orthree-dimensional map information for autonomous driving or assisteddriving of an automobile, the reception terminal may receive, inaddition to image data belonging to one or more layers, information on,for example, the weather or road construction as metadata, and associatethe metadata with the image data upon decoding. Note that metadata maybe assigned per layer and, alternatively, may simply be multiplexed withthe image data.

In such a case, since the automobile, drone, airplane, etc., includingthe reception terminal is mobile, the reception terminal can seamlesslyreceive and decode while switching between base stations among basestations ex106 through ex110 by transmitting information indicating theposition of the reception terminal upon reception request. Moreover, inaccordance with the selection made by the user, the situation of theuser, or the bandwidth of the connection, the reception terminal candynamically select to what extent the metadata is received or to whatextent the map information, for example, is updated.

With this, in content providing system ex100, the client can receive,decode, and reproduce, in real time, encoded information transmitted bythe user.

[Streaming of Individual Content]

In content providing system ex100, in addition to high image quality,long content distributed by a video distribution entity, unicast ormulticast streaming of low image quality, short content from anindividual is also possible. Moreover, such content from individuals islikely to further increase in popularity. The server may first performediting processing on the content before the encoding processing inorder to refine the individual content. This may be achieved with, forexample, the following configuration.

In real-time while capturing video or image content or after the contenthas been captured and accumulated, the server performs recognitionprocessing based on the raw or encoded data, such as capture errorprocessing, scene search processing, meaning analysis, and/or objectdetection processing. Then, based on the result of the recognitionprocessing, the server—either when prompted or automatically—edits thecontent, examples of which include: correction such as focus and/ormotion blur correction; removing low-priority scenes such as scenes thatare low in brightness compared to other pictures or out of focus; objectedge adjustment; and color tone adjustment. The server encodes theedited data based on the result of the editing. It is known thatexcessively long videos tend to receive fewer views. Accordingly, inorder to keep the content within a specific length that scales with thelength of the original video, the server may, in addition to thelow-priority scenes described above, automatically clip out scenes withlow movement based on an image processing result. Alternatively, theserver may generate and encode a video digest based on a result of ananalysis of the meaning of a scene.

Note that there are instances in which individual content may includecontent that infringes a copyright, moral right, portrait rights, etc.Such an instance may lead to an unfavorable situation for the creator,such as when content is shared beyond the scope intended by the creator.Accordingly, before encoding, the server may, for example, edit imagesso as to blur faces of people in the periphery of the screen or blur theinside of a house, for example. Moreover, the server may be configuredto recognize the faces of people other than a registered person inimages to be encoded, and when such faces appear in an image, forexample, apply a mosaic filter to the face of the person. Alternatively,as pre- or post-processing for encoding, the user may specify, forcopyright reasons, a region of an image including a person or a regionof the background be processed, and the server may process the specifiedregion by, for example, replacing the region with a different image orblurring the region. If the region includes a person, the person may betracked in the moving picture, and the head region may be replaced withanother image as the person moves.

Moreover, since there is a demand for real-time viewing of contentproduced by individuals, which tends to be small in data size, thedecoder first receives the base layer as the highest priority andperforms decoding and reproduction, although this may differ dependingon bandwidth. When the content is reproduced two or more times, such aswhen the decoder receives the enhancement layer during decoding andreproduction of the base layer and loops the reproduction, the decodermay reproduce a high image quality video including the enhancementlayer. If the stream is encoded using such scalable encoding, the videomay be low quality when in an unselected state or at the start of thevideo, but it can offer an experience in which the image quality of thestream progressively increases in an intelligent manner. This is notlimited to just scalable encoding; the same experience can be offered byconfiguring a single stream from a low quality stream reproduced for thefirst time and a second stream encoded using the first stream as areference.

[Other Usage Examples]

The encoding and decoding may be performed by LSI ex500, which istypically included in each terminal. LSI ex500 may be configured of asingle chip or a plurality of chips. Software for encoding and decodingmoving pictures may be integrated into some type of a recording medium(such as a CD-ROM, a flexible disk, or a hard disk) that is readable by,for example, computer ex111, and the encoding and decoding may beperformed using the software. Furthermore, when smartphone ex115 isequipped with a camera, the video data obtained by the camera may betransmitted. In this case, the video data is coded by LSI ex500 includedin smartphone ex115.

Note that LSI ex500 may be configured to download and activate anapplication. In such a case, the terminal first determines whether it iscompatible with the scheme used to encode the content or whether it iscapable of executing a specific service. When the terminal is notcompatible with the encoding scheme of the content or when the terminalis not capable of executing a specific service, the terminal firstdownloads a codec or application software then obtains and reproducesthe content.

Aside from the example of content providing system ex100 that usesinternet ex101, at least the moving picture encoder (image encoder) orthe moving picture decoder (image decoder) described in the aboveembodiments may be implemented in a digital broadcasting system. Thesame encoding processing and decoding processing may be applied totransmit and receive broadcast radio waves superimposed with multiplexedaudio and video data using, for example, a satellite, even though thisis geared toward multicast whereas unicast is easier with contentproviding system ex100.

[Hardware Configuration]

FIG. 32 illustrates smartphone ex115. FIG. 33 illustrates aconfiguration example of smartphone ex115. Smartphone ex115 includesantenna ex450 for transmitting and receiving radio waves to and frombase station ex110, camera ex465 capable of capturing video and stillimages, and display ex458 that displays decoded data, such as videocaptured by camera ex465 and video received by antenna ex450. Smartphoneex115 further includes user interface ex466 such as a touch panel, audiooutput unit ex457 such as a speaker for outputting speech or otheraudio, audio input unit ex456 such as a microphone for audio input,memory ex467 capable of storing decoded data such as captured video orstill images, recorded audio, received video or still images, and mail,as well as decoded data, and slot ex464 which is an interface for SIMex468 for authorizing access to a network and various data. Note thatexternal memory may be used instead of memory ex467.

Moreover, main controller ex460 which comprehensively controls displayex458 and user interface ex466, power supply circuit ex461, userinterface input controller ex462, video signal processor ex455, camerainterface ex463, display controller ex459, modulator/demodulator ex452,multiplexer/demultiplexer ex453, audio signal processor ex454, slotex464, and memory ex467 are connected via bus ex470.

When the user turns the power button of power supply circuit ex461 on,smartphone ex115 is powered on into an operable state by each componentbeing supplied with power from a battery pack.

Smartphone ex115 performs processing for, for example, calling and datatransmission, based on control performed by main controller ex460, whichincludes a CPU, ROM, and RAM. When making calls, an audio signalrecorded by audio input unit ex456 is converted into a digital audiosignal by audio signal processor ex454, and this is applied with spreadspectrum processing by modulator/demodulator ex452 and digital-analogconversion and frequency conversion processing by transmitter/receiverex451, and then transmitted via antenna ex450. The received data isamplified, frequency converted, and analog-digital converted, inversespread spectrum processed by modulator/demodulator ex452, converted intoan analog audio signal by audio signal processor ex454, and then outputfrom audio output unit ex457. In data transmission mode, text,still-image, or video data is transmitted by main controller ex460 viauser interface input controller ex462 as a result of operation of, forexample, user interface ex466 of the main body, and similar transmissionand reception processing is performed. In data transmission mode, whensending a video, still image, or video and audio, video signal processorex455 compression encodes, via the moving picture encoding methoddescribed in the above embodiments, a video signal stored in memoryex467 or a video signal input from camera ex465, and transmits theencoded video data to multiplexer/demultiplexer ex453. Moreover, audiosignal processor ex454 encodes an audio signal recorded by audio inputunit ex456 while camera ex465 is capturing, for example, a video orstill image, and transmits the encoded audio data tomultiplexer/demultiplexer ex453. Multiplexer/demultiplexer ex453multiplexes the encoded video data and encoded audio data using apredetermined scheme, modulates and converts the data usingmodulator/demodulator (modulator/demodulator circuit) ex452 andtransmitter/receiver ex451, and transmits the result via antenna ex450.

When video appended in an email or a chat, or a video linked from a webpage, for example, is received, in order to decode the multiplexed datareceived via antenna ex450, multiplexer/demultiplexer ex453demultiplexes the multiplexed data to divide the multiplexed data into abitstream of video data and a bitstream of audio data, supplies theencoded video data to video signal processor ex455 via synchronous busex470, and supplies the encoded audio data to audio signal processorex454 via synchronous bus ex470. Video signal processor ex455 decodesthe video signal using a moving picture decoding method corresponding tothe moving picture encoding method described in the above embodiments,and video or a still image included in the linked moving picture file isdisplayed on display ex458 via display controller ex459. Moreover, audiosignal processor ex454 decodes the audio signal and outputs audio fromaudio output unit ex457. Note that since real-time streaming is becomingmore and more popular, there are instances in which reproduction of theaudio may be socially inappropriate depending on the user's environment.Accordingly, as an initial value, a configuration in which only videodata is reproduced, i.e., the audio signal is not reproduced, ispreferable. Audio may be synchronized and reproduced only when an input,such as when the user clicks video data, is received.

Although smartphone ex115 was used in the above example, threeimplementations are conceivable: a transceiver terminal including bothan encoder and a decoder; a transmitter terminal including only anencoder; and a receiver terminal including only a decoder. Further, inthe description of the digital broadcasting system, an example is givenin which multiplexed data obtained as a result of video data beingmultiplexed with, for example, audio data, is received or transmitted,but the multiplexed data may be video data multiplexed with data otherthan audio data, such as text data related to the video. Moreover, thevideo data itself rather than multiplexed data maybe received ortransmitted.

Although main controller ex460 including a CPU is described ascontrolling the encoding or decoding processes, terminals often includeGPUs. Accordingly, a configuration is acceptable in which a large areais processed at once by making use of the performance ability of the GPUvia memory shared by the CPU and GPU or memory including an address thatis managed so as to allow common usage by the CPU and GPU. This makes itpossible to shorten encoding time, maintain the real-time nature of thestream, and reduce delay. In particular, processing relating to motionestimation, deblocking filtering, sample adaptive offset (SAO), andtransformation/quantization can be effectively carried out by the GPUinstead of the CPU in units of, for example pictures, all at once.

INDUSTRIAL APPLICABILITY

The present disclosure is applicable to, for example, televisionreceivers, digital video recorders, car navigation systems, mobilephones, digital cameras, digital video cameras, video conferencesystems, and electron mirrors.

The invention claimed is:
 1. An encoder, comprising: circuitry; andmemory, wherein using the memory, the circuitry: generates areconstructed image by encoding and decoding an original image;performs, on a current block included in the reconstructed image, filterprocessing that is applied to all pixels in the current block, when anedge intensity of the current block is lower than a threshold; and skipsthe filter processing on the current block when the edge intensity ofthe current block is higher than the threshold, wherein the edgeintensity of the current block is calculated from values of peripheralpixels.
 2. The encoder according to claim 1, wherein in the filterprocessing, filters to be used are associated with groups that areranges of edge intensities, a group that includes the edge intensity ofthe current block is determined from among the groups, and one of thefilters that is associated with the group determined to include the edgeintensity of the current block is used for the current block.
 3. Theencoder according to claim 2, wherein in determining the group, the edgeintensity is clipped to a predetermined value, and a group that includesthe edge intensity clipped is determined, the filter processing isperformed on the current block when the edge intensity before beingclipped is lower than the threshold, and the filter processing on thecurrent block is skipped when the edge intensity before being clipped ishigher than the threshold.
 4. The encoder according to claim 3, whereinthe threshold is higher than the predetermined value.
 5. The encoderaccording to claim 1, wherein the circuitry further determines thethreshold, and generates an encoded bitstream that includes informationindicating the threshold determined.
 6. The encoder according to claim1, wherein the circuitry further: calculates, based on edge intensitiesof blocks included in a processing unit, a statistic of the edgeintensities for the processing unit; and performs the filter processingon all the blocks included in the processing unit when the statisticsatisfies a predetermined condition.
 7. The encoder according to claim1, wherein the circuitry further determines a parameter for the filterprocessing for the current block, based on an electro-optical transferfunction (EOTF) of the original image.
 8. A decoder, comprising:circuitry; and memory, wherein using the memory, the circuitry:generates a reconstructed image by decoding encoded data; performs, on acurrent block included in the reconstructed image, filter processingthat is applied to all pixels in the current block, when an edgeintensity of the current block is lower than a threshold; and skips thefilter processing on the current block when the edge intensity of thecurrent block is higher than the threshold, wherein the edge intensityof the current block is calculated from values of peripheral pixels. 9.The decoder according to claim 8, wherein in the filter processing,filters to be used are associated with groups that are ranges of edgeintensities, a group that includes the edge intensity of the currentblock is determined from among the groups, and one of the filters thatis associated with the group determined to include the edge intensity ofthe current block is used for the current block.
 10. The decoderaccording to claim 9, wherein in determining the group, the edgeintensity is clipped to a predetermined value, and a group that includesthe edge intensity clipped is determined, the filter processing isperformed on the current block when the edge intensity before beingclipped is lower than the threshold, and the filter processing on thecurrent block is skipped when the edge intensity before being clipped ishigher than the threshold.
 11. The decoder according to claim 10,wherein the threshold is higher than the predetermined value.
 12. Thedecoder according to claim 10, wherein the circuitry further obtainsinformation indicating the threshold from an encoded bitstream thatincludes the encoded data.
 13. The decoder according to claim 8, whereinthe circuitry further: calculates, based on edge intensities of blocksincluded in a processing unit, a statistic of the edge intensities forthe processing unit; and performs the filter processing on all theblocks included in the processing unit when the statistic satisfies apredetermined condition.
 14. The decoder according to claim 8, whereinthe circuitry further determines a parameter for the filter processingfor the current block, based on an electro-optical transfer function(EOTF) of the reconstructed image.
 15. An encoding method, comprising:generating a reconstructed image by encoding and decoding an originalimage; performing, on a current block included in the reconstructedimage, filter processing that is applied to all pixels in the currentblock, when an edge intensity of the current block is lower than athreshold; and skipping the filter processing on the current block whenthe edge intensity of the current block is higher than the threshold,wherein the edge intensity of the current block is calculated fromvalues of peripheral pixels.
 16. A decoding method, comprising:generating a reconstructed image by decoding encoded data; performing,on a current block included in the reconstructed image, filterprocessing that is applied to all pixels in the current block, when anedge intensity of the current block is lower than a threshold; andskipping the filter processing on the current block when the edgeintensity of the current block is higher than the threshold, wherein theedge intensity of the current block is calculated from values ofperipheral pixels.